Behind the first massively multiplayer virtual world was a home computer that was comically underpowered by today’s standards. Introduced in November 1982, the Commodore 64 was named for its then-generous 64 kilobytes of memory. In its twelve years on the market, it became the best-selling desktop computer in history. A conservative estimate puts its sales at 12.5 million machines worldwide.

The C64 sold for $595 in the US, compared to about $1500 for an Apple II with just 48 kilobytes of memory, and £399 in the UK. The computer, which looked like a thick keyboard, could use a TV as a monitor. Its operating system and the BASIC programming language were built into its hardware, requiring no disk to boot up. Typical for the time, an external drive to store and read software on floppy disks cost extra. Commodore, declared CEO Jack Tramiel, made ‘computers for the masses, not the classes’.

The C64’s low price was made possible by an unusual selection of chips. The CPU was a cheap, efficient, stripped-down industrial controller. The sound chip was designed for music synthesizers, the graphics chip for video games. The result was an inexpensive machine whose sound and 16-color palette were ahead of their time.

Subscribe now

In the 1980s, its gaming chops made the C64 low status. ‘The dismissive label of “game machine” implied that because the C64 was good for playing games, it was “too much fun” to take seriously and could not also be used for ‘serious’ things like word processing (which it was used for)’, writes video game scholar Jesper Juul in Too Much Fun, a 2024 history of the Commodore 64. ‘The label also meant that if you wanted to be “serious”, you should get a much more expensive computer with nearly identical capabilities except for the ability to play good games’.

But the C64’s cultural implications were quite serious. It helped move video gaming out of arcades, where sessions had to end quickly so players would feed more coins into the machines. It permitted open-ended play at home, enabling a far wider range of games, including one that heralded, for good and ill, today’s hyperconnected world.

Four years after the C64’s introduction, a cosmetically refreshed version dubbed the Commodore 64C came bundled with new software, including a word processor, and offered the option of a Mac-like icon-based operating system. Crucially, it included a telecom program connecting C64 users to a dedicated information network called QuantumLink. Known familiarly as Q-Link, the system offered access at significantly lower prices than competitors like CompuServe.

By buying transmission capacity after business hours, the company paid pennies on the dollar. Unlike its competitors’ terminal setup, it also used then-exotic client-server architecture, requiring less back-and-forth transmission and permitting more users at the same cost. The result was a connection price that started at $3 an hour in 1986, when the business-oriented CompuServe was charging $8 off-peak and $22.50 during weekdays. (Q-Link’s hourly rate soon rose to $3.60 and eventually higher still but remained cheaper than competitors.)

Q-Link encouraged real-time interactions among C64 owners. Like CompuServe subscribers, they could use online chat, join forums, and play games together, including chess, blackjack, and hangman, with other users. But Q-Link’s most revolutionary game took a few more years to roll out. Developed at Lucasfilm’s games division, it was called Habitat.

Observers at the time, including Q-Link’s marketing team, had trouble explaining what it was. One journalist called Habitat a ‘world simulation game’, another ‘an adventure game…which will involve players from all over the country playing the game at the same time’. A feature in Compute! magazine described it as ‘an intriguing combination of telegaming and straight online chatting’. Author Kathy Yakal wrote that ‘Habitat, unique to this point in the history of computer entertainment, is an early version of the kind of entertainment often predicted by industry futurists: the interactive motion picture’.

Subscribe to print

Unlike a movie, however, Habitat had no plot, and unlike an adventure game, it had no goal. It instead offered the tools with which to create a mini-society.

‘It’s the first virtual world’, says Alex Handy, founder of the Museum of Art and Digital Entertainment (MADE), a video game museum in Oakland featuring playable exhibits and demos. ‘It was the source of almost all of the original terms that have to do with online worlds’.

Habitat introduced the term avatar as now used in online contexts. It offered the first in-game currency – players got 2,000 tokens when they started and 100 more each day they logged on – and the first chance for players to buy and sell among themselves. It let them customize their avatars. ‘It was the first time you could pay for cosmetics in a game, which is a multibillion-dollar industry now’, says Handy. Players owned houses they could decorate. They gathered at the central fountain and chatted in speech balloons with other avatars. They threw parties. One published a newspaper called ‘The Rant’. Another started a church, The Order of the Holy Walnut.

The game ‘was deliberately open ended and pluralistic’, creators Chip Morningstar and F Randall Farmer explained in a 1990 paper called ‘The Lessons of Lucasfilm’s Habitat’.

With such open-ended possibilities, even testing with a few hundred participants produced unpredictable outcomes. A puzzle-based treasure hunt took weeks to build. One player solved it in just eight hours, before many others could even get started. ‘The result was that one person had had a wonderful experience, dozens of others were left bewildered, and a huge investment in design and setup time had been consumed in an eyeblink’, wrote Morningstar and Farmer. They had to stop thinking like traditional game designers and more like rule makers.

In another case of unintended consequences, players discovered an arbitrage opportunity. The game included machines called Vendroids, where players could buy items like storage chests or avatar heads, and Pawn Machines, where they could sell them back. Often referred to as vendos, the vending machines were another Habitat first. They produced the items on demand, with no production cost. To make play more lifelike, prices varied from place to place.

But the creators made a mistake. They priced dolls at 75 tokens at one Vendroid and 100T at a Pawn Machine across town. Worse, crystal balls were for sale in one place at 18,000T and could be hocked at 30,000T in another. A few wily players spent hours going back and forth buying and selling dolls, then used their profits to do the same with crystal balls. Each wound up with hundreds of thousands of tokens, quintupling Habitat’s money supply overnight.

‘I gotta say, that was a Monday morning I’ll never forget in my life’, says Farmer. It was the first example of what is now known as a ‘dupe bug’, or money in a game seemingly coming out of nowhere.

When asked about their suddenly expanded bank balances, the arbitrageurs replied, ‘We got it fair and square! And we’re not going to tell you how!’ They eventually explained, and the bug was fixed. Farmer, who served as Habitat’s administrator (‘the Oracle’), communicating with players, let them keep the money. They used it to sponsor treasure hunt games for the community, giving the incident a constructive conclusion.

Subscribe now

A happier surprise was the spontaneous emergence of performing arts groups. To coordinate their movements despite the latency of their slow connections, performers practiced using stopwatches and telephone calls. ‘It looked like it was done in synchrony when in fact it was all wildly asynchronous and decoupled’, Morningstar recalled in a 2022 interview. ‘The fact that people would go to the kinds of lengths that were required, the kinds of obsessive attention to detail, to engage in that kind of creativity – it speaks to something very powerful about people’s drive to interact with each other and be creative.’

Such devotion is all the more impressive when you consider that by 1988, when paid beta testing began, players were paying $4.80 an hour for connection time. Some enthusiasts ran into trouble. A teenage tester ran up a $600 bill in a month, leading his father to demand that he quit. Another player complained that Habitat had made Q-Link too expensive. In his first two years on Q-Link, he’d spent just $35 total. ‘But in the last month, while I was playing Habitat I spent $270!!! I can’t afford that’, he wrote. ‘You need to make it cheaper’.

Habitat was a remarkable technological achievement, built on a platform with just 64 kilobytes of memory and 100 kilobytes of disk space, using 300-baud modems that sent 30 characters a second. Creating the impression of rich visual interaction was almost a magic trick under these conditions. It required an innovative allocation of most code to the server, with the player’s client using a simple list of object definitions and commands like GET. ‘​​That really helped keep things speedy’, says Stuart Cass, known online as Stublad, who serves as Habitat’s volunteer archivist and historian. ‘This kind of technical model became much more commonplace later on but it was still novel at the time.’

Announced in 1986, the game didn’t reach the general public until 1989 because the problems were both difficult and novel. ‘Debugging distributed systems was a new thing’, explains Morningstar in an email, and ‘introducing a population of humans into the picture added an entire new tier of testing and debugging that nobody anticipated (even though in retrospect it should have been obvious) and nobody had any experience with, so we had to learn as we went. A couple of very big learning curves to overcome.’

Farmer puts it succinctly: ‘We did the impossible.’

When Habitat finally launched for all Q-Link subscribers, the company rebranded the game as Club Caribe, eliminating the pilot test’s weapons and magic wands and some of its fantastic elements. The change saved money, and framing the world’s open-ended play as an island vacation seemed more understandable to a mass audience. Much of the code remained unchanged, however, and soon some of the weirder features, including alien avatar heads, reappeared.

Club Caribe had its own special qualities, including a ‘nude beach’ where the avatars’ clothing was replaced with pink pixels, only to reappear once they left the area. Penguin races were popular sports. ‘Wave teams’ held monthly competitions, performing slow-motion routines that looked ‘very much like cheerleading on Valium’, combining steps, gestures, and text.

Subscribe to print

Long before social media, Habitat revealed the complexities and dangers of online interactions among many individuals. Some players proved upstanding members of the community, while others went rogue. Different people have different goals, personalities, and moral codes, and Habitat demonstrated that in an online setting ‘people will do everything that can possibly be done – good, bad, evil, neutral, weird, crazy’, says Handy, whose museum has organized the game’s rebirth as Neohabitat.

Farmer and Morningstar, he says, ‘learned from Habitat that people are kind of horrible, and if they’re given anonymity and free rein, they will do horrible things, and they will do against-the-rules things, but they will also do wonderful things and form communities. It’s like some kind of weird coral reef phenomenon where you get wonderfully delicious fish and super-poisonous fish. They’re all there. You don’t get to choose. It all comes together.’

Virginia Postrel is a contributing editor and author at Works in Progress.
Illustration by Dan Cox.

Alex Chalmers and Rob Wiblin explain why recycling isn’t quite what it seems.

Every child is taught that landfill is the worst place our trash can end up. It is the sad consequence of a failure to recycle: a mountain of waste leaking chemicals and smells, blighting the land forever.

What if that picture is wrong? What if landfill, properly done, is actually one of the cleanest, cheapest, and most environmentally sensible things we can do with our waste? It turns out that for much of what we throw away, the humble landfill beats the recycling bin.

Single-use is often better

The case against landfill has two parts. The first part is that there are efficient, cheap, or environmentally friendly ways to practically reuse or recycle materials, rather than landfilling, meaning that there is a reasonable alternative. The second is that landfill itself is unsustainable, or environmentally unfriendly, meaning that we need an alternative. Both are false.

It’s natural to assume that reusable always means better. But this intuition treats different materials as interchangeable and ignores the cost of making them in the first place. Once we account for energy, labor, and other inputs, reuse pays off only in selective cases.

Subscribe now

Producing tiny slivers of plastic uses almost no energy. Making the polyethylene resin for a single thin plastic bag, then blowing and sealing it, uses something like 0.6 megajoules, roughly the same energy as boiling a kettle of water. By contrast, cotton is extremely energy intensive, partly because cotton bags need to be much thicker to work, and weigh around 200 grams as compared to eight grams for polyethylene. Instead of a simple blowing and sealing process, the cotton must be made into yarn, woven into fabric, prepared, dried, sized, dyed, and finished, which takes around 17.5 megajoules, around 29 times as much energy.

In total, Britain’s Environment Agency calculated that a conventional cotton bag needed to be reused 173 times to beat plastic. Denmark’s equivalent public body estimated a similar ratio. Sufficiently well-worn cotton tote bags can beat plastic for environmental cost, but only for the most consistent among us.

The same pattern shows up almost everywhere we have tried to replace disposable goods with durable ones. Steel is more energy intensive than plastic, and a steel straw requires 10 grams of steel, compared to just 0.2 grams of plastic for a plastic straw. So even if the steel is never washed (hot water is also energy intensive), it would take 150 reuses for a steel straw to use fewer resources than a plastic one. And who would go without washing it?

A ceramic mug only beats a polystyrene cup on energy use after 1,000 uses, and even then only if your dishwasher is fairly efficient. Run a less efficient one and the disposable cup wins on energy forever. Cloth diapers feel greener than disposables, but once you account for the cotton, the laundering, the hot water, and the detergent, the UK Environment Agency found the two are roughly tied in overall demand on resources. A returnable milk bottle takes much more energy to produce and much more fuel to transport than a plastic carton, and has to make around ten or more trips to use less energy than a bottle made from polyethylene plastic.

The case for recycling to avoid using virgin material is much stronger when it comes to metals. Recycling 1 kilogram of steel saves 1.4 kilograms of iron ore and uses 65 percent less energy. For aluminum, the energy savings from recycling can be as high as 95 percent. This is because making metal from scratch requires extremely energy-intensive chemical reduction of ores, while recycling primarily involves remelting metals already in their elemental form. Because recycling metals is cheaper than mining, refining, and smelting new ones, the world does an awful lot of it. About 30 percent of the metal used in steel production globally is now recycled scrap.

Are we running out of materials?

The best case for recycling is where the materials themselves are scarce, and we can more cheaply reuse them than finding more of them. Batteries and electronics contain metals like copper, cobalt, lithium, and nickel. While we are not about to run out of any of these materials globally in a strict sense, their supplies are limited in practical terms. Plenty of copper ore remains in the ground, but it is getting harder and more expensive to extract as the highest quality and most accessible deposits have been depleted. In the case of cobalt, lithium, and nickel, production is geographically concentrated, meaning countries without natural supplies of their own have an interest in recycling in order to limit their dependence on imports. All of these, especially copper and nickel, are highly recyclable, with little loss of quality over multiple reuses. For these, recycling is sensible.

By contrast, there is no danger of running out of paper. We can always grow more trees, and that is in fact a decent way of removing carbon from the atmosphere. The silicon used to make glass is one of the most abundant elements on Earth.

American plastic comes from ethane, extracted from natural gas. The alternative to making plastic with it is to leave it in the gas stream, slightly increasing the heat it generates. One kilogram of ethane, left in the stream and made into electricity, could power a typical US house for a few hours, or it could be made into 100 shopping bags. The US has estimated reserves of gas that could last for nearly a century at current rates, and this could increase further with the discovery of new deposits.

Share

The rest of the world makes plastics from propane, butane, and naphtha, meaning from crude oil. We will eventually exhaust this source, but not anytime soon. What’s more, plastics use very little, which is why carrier bags are still so cheap. One 13-kilogram propane cylinder, the kind a family might use to power their gas grill, could instead be made into about 1,600 typical eight-gram plastic carrier bags, three years of a family’s ten-shopping-bag weekly shops.

There ain’t no such thing as a free recycle

Recycling is a straightforward process conceptually: collect waste, reprocess it, and turn it back into useful material. That picture breaks down once you look at what happens to waste after collection. Much of what is sent for recycling is never recycled. About 25 percent of items placed in American recycling bins are contaminants: for example, lids on containers, food, or damp paper. The number may be even higher, as the vast majority of US states do not consistently track contamination data. This can make the process energy or labor intensive and therefore expensive.

Reducing the contamination rate is challenging. Education programs have proven largely ineffective. The best single method for discouraging recycling contamination is cart tagging, where waste collection crews check the contents of a recycling bin and leave it unemptied if contaminated, affixing a tag explaining what was wrong. Despite being the single most forceful and labor-intensive curbside method, a cart-tagging program in Ohio succeeded in reducing contamination by only 29 percent over five rounds.

The imperfect recycling process means that putting low-value plastics (such as plastic film, black plastic food trays, or small items like bottle caps and straws) into the recycling bin can sometimes be actively harmful. Since these items are hard to recycle and are often screened out and sent to landfill, they may actually add to the contamination rate (as well as the time and labor needed for processing) without ever becoming useful recycled material.

Many mid-value plastics, like the polypropylene used in plastic bottles or butter tubs, require intensive washing. This removes contaminants but also detaches potentially recyclable plastic fragments, meaning the resulting mulch must be filtered. After the washing, the plastic is melted and filtered for contaminants a second time before being turned into pellets. Yield losses can be as high as 45 percent.

Subscribe now

While the environmental case can hold up for things like plastic soda bottles, where minimal processing is needed, it quickly drops off as you go down the quality scale. For mid-quality plastics like butter and margarine tubs, recycling one ton of plastic prevents the emission of 0.43 tons of carbon dioxide compared with using virgin material. At the same time, recycled tub-grade plastic typically costs hundreds of dollars more per ton than virgin plastic. This means that consumers are effectively paying over a thousand dollars to save one ton of carbon dioxide. By contrast, direct air capture, which removes carbon dioxide from the atmosphere, currently costs an average of $490 per ton, and area specialists hope to lower the cost to $100 per ton in the coming decades. Recycling has its virtues, but recycling plastic to save energy just doesn’t add up.

Your plastic toothbrush isn’t killing turtles

Pro-recycling campaigns portray a world where unrecycled plastic bags, straws, and toothbrushes choke the world’s oceans. This worry has led governments to restrict or disincentivize single-use plastics. But much of this is environmental theater.

Richer countries have near-universal refuse collection and almost none of their waste winds up in the ocean. In low-income countries, however, over 90 percent of waste is improperly managed, and typically ends up dumped, burned, or escaping into waterways. Plastic flows into the ocean overwhelmingly come from a small handful of rapidly growing Asian economies. Approximately a hundred rivers, mostly in South and South-East Asia, account for half of ocean plastic. And a substantial share of plastic in the ocean isn’t domestic waste at all, but rather discarded fishing gear.

Ocean litter is a huge environmental problem, and solving it means building cheap, effective, and safe waste management in those countries where it originates (plus perhaps cleaning the oceans up). If you live in a Western country, throwing your trash into the recycling bin rather than general waste makes no difference at all to the amount of flotsam in the ocean: whichever bin you choose, that’s not where it will end up.

Landfill is pretty clean

Even though recycling or reuse is energy intensive, it would be worth doing it if landfill was an environmental disaster. But most people’s image of landfill is severely out of date. They envisage a rotting mound of waste, dumped in an open hole in the ground and leaching dangerous chemicals into the soil. In most of the developed world, this hasn’t been true for decades. Engineers build modern landfills on thick layers of clay and tough plastic liners that contain the contaminated liquid that forms when rainwater filters through decomposing waste.

Operators place waste in thin layers, compact it tightly, and cover it regularly to control smells, litter, pests, and fire risk. As food and garden waste break down, gas wells pull methane out of the landfill body and route it to flares or generators instead of letting it escape into the air. This typically captures around 75 percent of the methane produced, and sometimes as much as 95 percent. Drainage layers and pipes collect contaminated liquid and send it for treatment, while operators monitor the surrounding ground and water, both throughout the site’s life and long after it closes. Regulators shut down badly run landfills.

Much of the leakage that happens in landfills is from legacy sites with poorer liner systems. New York’s environmental regulator reviewed groundwater monitoring for 31 post-1988 landfills, which had collectively operated for about 450 years, and found no adverse impact on groundwater quality.

Out of the garbage can, into the fire

There is another option: burning trash. Perhaps counterintuitively, this can be a very environmentally friendly option and has the advantage of reducing the waste dramatically in volume. Controlled incineration, which burns waste in a sealed, high-temperature furnace, uses systems to catch pollutants, and is more efficient than landfill at containing methane, preventing virtually any from escaping. On top of all this, the heat released can be used to generate electricity.

Unfortunately, controlled burning is more expensive than landfill. In the US, landfill is reliably 20–30 percent cheaper. While it is possible to reduce costs by selling the electricity generated, modern incinerators are among the most expensive power plants to build per megawatt, in some cases costing an order of magnitude more than a conventional natural gas plant.

This is because burning trash comes with specific complexities. The smoke from burning trash contains mercury, lead, and acid gases, requiring expensive pollution control. The acid gases produced would dissolve normal steel, so the boilers have to be lined with either specialized ceramics or a nickel-chromium alloy. This means most municipalities opt for comparatively inexpensive landfill instead.

Subscribe now

Cheap, uncontrolled burning is bad for both the environment and human health; up to 10 percent of air pollution in Delhi comes from incinerating waste, and burning crops during the stubble-burning season contributes another 30 percentage points.

It’s okay to be a landfiller

Every year, around 500 million tons of waste are recycled. US recycling rates have more than tripled since 1980, while close to 50 percent of all waste in the European Union is now recycled. Increasing this number sits at the heart of major international environmental strategies. Yet this is unnecessary and will make us poorer in the long run. Much of the time, we should bury the waste instead.

In the developed world, though there are benefits to recycling, other waste disposal options are perfectly good alternatives. Modern, well-run landfills cause minimal environmental damage. We have plenty of space to put them – less than 0.01 percent of the US is used for landfill, less than 0.001 percent of Australia is, and only about 0.02 percent of Germany is. We can even build on top of old landfills, so the land area is not spent permanently. Nor are we about to run out of most of the materials commonly recycled. And because it is less resource-intensive, landfill is far cheaper than recycling.

Instead of paying more to recycle, we could spend that money far more effectively on other environmental mitigation measures like carbon capture. The main exception is metal recycling, which should likely be the primary or even exclusive focus of municipal recycling programs. Inasmuch as some landfill sites fall short of best practices, as some surely still do, improving monitoring and imposing penalties on sloppy operators is likely to pack a much bigger environmental benefit, at lower cost, than trying to divert more materials from landfill to recycling.

And while modern landfill is ideal, worse-run landfill is still an upgrade in regions where the alternative is open waste dumping or burning. It reduces human contact with waste and localizes pollution to one managed site instead of many unmanaged ones.

Subscribe to print

There is a great humanitarian and environmental case for improving waste disposal systems in developing countries. But focusing effort on expensive recycling means getting less bang for our buck. Recycling is complex to sustain: it requires the successful coordination of collection, separation, contamination control, and reliable buyers for the material. If even one part of the chain breaks down, it doesn’t work. By contrast, landfill is simple and cheap. Investing in landfill, even suboptimal landfills, protects more local rivers, forests, lakes, and seas.

Alex Chalmers is a staff writer at the Cosmos Institute.

Rob Wiblin is the host of The 80,000 Hours Podcast.

The text of the article incorrectly stated that making a cotton bag required 1,725 megajoules of energy. In reality, it requires about 17.5 megajoules. The dataviz used the correct data. The article has been corrected.

A car is a difficult thing to steal. It is large, cherished by its owner, difficult to hide and required by law to have identifying metal plates that everyone can see. A good thief changes the plates, and an excellent thief steals a common car in a boring color and hopes to blend in among the crowd. But eventually, no matter what techniques they use, they must drive that car on the road, and roads are public places.

But until recently, finding a stolen car and catching its thief depended on a diligent police officer looking at the right road at the right moment and managing to copy down a license plate number going past at speed, and then remembering he had seen it on the morning briefing’s stolen car hot sheet. America has four million miles of public roads, and almost 50 percent of the country’s police departments employ fewer than ten full-time officers. The odds were in the thief’s favor.

With not much to go on, police officers were forced to operate on vague descriptions and partial plates. While I pulled over a car that happened to be the same color as the suspect’s vehicle, and spent time checking names and licenses; the criminal was usually somewhere else. Imprecision allowed thieves to escape while intruding on the lives of millions of innocent motorists. That is, until the arrival of systems like Flock.

Bare ALPR

Flock Safety, a startup based in Atlanta, Georgia, was founded in 2017 to give police departments better eyes. Its product is a small solar-powered automatic license plate recognition (ALPR) camera attached to a pole on the roadside. As a car passes, the device takes a photograph of the vehicle, notes identifying features like color and make, and reads its license plate. The license plate is instantly checked against the FBI’s national database of stolen cars or wanted persons. If there’s a match, it sends an alert to police officers in the area, who may be eating their lunch instead of watching the road. As a police officer in the southeastern United States, I have often used Flock to catch wanted criminals.

But ALPR is not new. Originally developed in 1976 by the British Home Office, it was deployed as a prototype on toll roads and tunnels, leading to the first ALPR-enabled arrest in 1981 when a stolen car being driven by its thief was found. The first large-scale trial of the technology was ‘Project Laser’ in 2004, when the project’s cameras read more than five million British plates, resulting in 3,071 arrests. Just a year later, ALPR was used to locate a man who murdered a female police officer. At the time, Chief Superintendent Geoff Dodd of the West Yorkshire Police described it as ‘the best investigative tool we have had since the introduction of DNA analysis’.

Criminals have learned to fear the technology. In London, where I spent five years as a police officer before moving to America, ALPR is so thoroughly embedded in criminal life that rappers discuss it in their lyrics. ‘Bare A[L]PR, bro,’ the artist Central Cee raps, ‘beg you don’t smoke weed in the car’.

For much of the technology’s history, however, it has needed expensive installations or cameras attached to police vehicles, affordable to only the largest departments. Alerts were often neither instant nor accurate. Flock’s idea was to sell a more accurate ALPR camera for an annual subscription of just $3,000, an affordable price given that the typical US police department has an annual budget of $1 million. It worked, and today almost 30 percent of police agencies in the United States subscribe to the service.

It is easiest to imagine the Flock camera, or any ALPR device, as a roadside barcode scanner. I can use a ‘lookup’ tool for either a plate or vehicle description that could be connected to a specific investigation. For instance if a victim of a sexual assault told me the suspect was driving a white Toyota Tacoma with a roof rack, I could while still on scene conduct a lookup in the area filtered for similar vehicles with roof racks and see results from within a particular timeframe. For each search, I am required to record a case number and a reason that is then published in a monthly audit sent to and validated by department administrators.

I have used Flock myself, for instance, to locate a vehicle involved in a hit and run when all there was to go on was a model and color. Using that and an approximate time window, I was able to find an image from when a car entered my jurisdiction, and when it left, with the visible addition of a significant dent from the collision.

What Flock cannot do is search for individuals or show who is driving a particular vehicle that it scans. An ALPR camera does not care about the person driving a car, or its passengers, and even if an officer gets an alert that a vehicle is known to be driven by a wanted felon they must themselves establish who is behind the wheel before having probable cause to stop it.

Stolen cars provide the clearest evidence such a scanner works. American police solve only 8.2 percent of reported vehicle thefts with an arrest. A recent working paper suggests that agencies that adopted the devices saw a 15.9 percent relative increase in car thefts caught, which would raise the national rate to 9.5 percent. But that is just stolen cars.

Vehicle crime takes many forms. It is often the means by which a robber or a murderer arrives at and departs from their crimes. Criminals’ vehicles carry drugs and guns, and smuggle cash. In Atlantic City, New Jersey, vehicles were involved in 53 percent of shootings during the two years before the city expanded its ALPR network. After the expansion, Atlantic City saw monthly averages of motor vehicle thefts drop by 20 percent, property crimes by 34 percent and fatal shootings by almost 40 percent. Seventy-two alert-caused traffic stops located forty stolen vehicles and nine stolen plates.

Flock itself conducted a study claiming that 10 percent of all reported crime in the United States is solved using evidence obtained from their cameras. Not bad for a few thousand dollars a year.

On several occasions, Flock alerts have allowed me to arrest those suspected of serious violent crimes. Local officers knew who they were and had circulated information about what cars they drove to neighboring agencies. Besides automatically cross-referencing from national databases, officers can create their own ‘hotlists’ of license plates that will create alerts, even if they are not on FBI-maintained lists.

These could be hotlists to build intelligence on drug supply or gangs, or plates belonging to drivers in the city with suspended licenses. These officer-created hotlists can be shared locally or nationally, but still require an officer to verify the information and establish lawful reasons to investigate the cars involved. Without those alerts, some of the criminals I arrested would have remained free for longer.

Share

Good Flock, Bad Flock

And yet, the past month has seen this simple piece of crime-fighting technology become the most reviled piece of street furniture in America. Flock cameras have been sawn from their poles, hammered into shards by teenagers, and rammed by vehicles. Cities have canceled contracts even where their own audits found no evidence that their officers had misused the system. Opposition stretches from Bernie Sanders all the way to the former WWE wrestler Kane, who now serves as the Republican mayor of Knox County, Tennessee, and who describes Flock as ‘unconstitutional’.

More than 150 cities and towns have now deactivated their Flock cameras or canceled contracts with the company. Over the space of a few weeks a startup previously known to just police officers and neighborhood associations has joined data centers, Covid vaccines, 5G towers, pasteurized milk and fracking in the pantheon of American moral panics.

Opponents of Flock tend to believe that it is abused by policemen with impunity, that it can track individuals as well as cars, and that it violates American constitutional protections. None of those things are true.

Obviously a camera capable of finding a stolen car is also capable of finding a car driven by somebody’s ex-wife and so like any software, Flock has been abused. There are stories of police officers who have used it to stalk girlfriends, and there are also innocent motorists who have been stopped by police after Flock cameras misread plates or received old information from national databases. A common issue from my experience is stolen front license plates being entered into a database and the innocent owners of the rear license plate being held on suspicion of car theft.

But Flock comes with protections. As mentioned earlier, each search in Flock must be accompanied by a recorded reason. Similarly entering a plate into a hotlist must have a case number assigned. Results were originally retained for thirty days, but recent changes by Flock mean that recorded plates are now kept for only seven days. Suspicious searches are picked up by algorithms or found in department audits, with the service blocking users until senior officers evaluate and resolve flags. The Institute for Justice, a think tank that is critical of ALPR, studied misuse of Flock in April of this year and found 51 incidents across the United States since 2024, noting that ‘Nearly all of these officers were criminally charged and lost their jobs, either by resigning or getting fired’. Another incorrect belief is that Flock does more than scan vehicles, with some suggesting it scans and tracks passing phones or devices – but it does no such thing.

While Flock is a tool that can be audited, there is nothing to stop a corrupt officer simply following a car when they don’t like the look of its driver, or writing down plates of vehicles spotted outside an ex-girlfriend’s house – they would just be harder to catch. And Flock does not proactively alert officers to cars that do not trigger flags on national or local hotlists. There is no reason state legislatures or Congress could not create harsh punishment or penalties for abuse of ALPR, without getting rid of it entirely.

Another argument against Flock, as espoused by Kane, is that it violates liberties granted by the Fourth Amendment, protecting citizens from unreasonable privacy breaches from law enforcement. But it has been repeatedly established over the last century by courts across the country that cops observing license plates, either with the naked eye or by machine, is not an unreasonable search. After all, your license plate belongs to the government and a highway is a public place.

In 1983, the Supreme Court held unanimously that ‘a person travelling in an automobile on public thoroughfares has no reasonable expectation of privacy in his movements from one place to another’. And in January of 2026, a federal judge in Virginia ruled in a challenge by two civil rights activists against Flock specifically that: ‘An individual scan of a license plate, a vehicle identifier that generally must be displayed under state law, does not invade any privacy interests’.

The problem for Flock is that, if it works, it provides no visible benefits outside the crime statistics: a crime prevented because an offender was afraid of being caught by ALPR produces no victim and no police report. But every misuse has a victim who can describe what happened and a mugshot of a corrupt cop, and every false alert can produce a photograph of an innocent motorist in handcuffs.

Flock did not invent its capabilities and certainly does not have a monopoly on them. There are at least five other companies that offer almost identical products and services to public and private enterprise, some arguably even more invasive. Even some of the cities that have canceled contracts with Flock Safety in recent weeks have signed up to buy similar products from the company’s rivals.

It seems unlikely that America will ever ban ALPR at a state level, let alone a national one. Instead, a patchwork already familiar to American policing will result, where policies and practices diverge across local and political boundaries.

Nor would the cameras actually disappear, even in towns where governments restrict their use and cancel contracts. The already-mentioned Fourth Amendment only applies to the government, not to private enterprise. Police departments may dismantle their networks but homeowners associations concerned about vehicle theft can buy their own network of Flock cameras, as many already do. The people harmed the most will be the residents of the average small town whose police departments cannot afford helicopters, drones or enough police officers to watch every road themselves.

I can remember policing without ALPR. A circulation would go out over the radio to look for a silver Volkswagen Golf, no license plate seen, and so for the rest of the night every single silver Golf we saw got stopped. There was no audit trail of our mistakes because there was no software.

Even when ALPR was introduced, we relied on a complex system that would send alerts through multiple layers of human filtering before finally being sent out to officers – often five to ten minutes after the car had been detected – and so was usually long gone by the time we turned up. With Flock, I can get a notification on my phone and can set my patrol car up to intercept it as it approaches.

Flock’s critics have the important point right: we should want the police to invade law-abiding citizens’ lives as little as possible. But they are mistaken about what Flock actually does. Flock allows us to be more surgical and precise, avoiding pulling over innocent people with all of the risks that involves. More than anything, Flock allows me to leave you alone.

Ned Donovan is a policeman

Subscribe now

Miriam Pinski explains why buses can’t solve all our problems.

We ask public transport to address problems it was never designed to solve. Bikeshare services are charged with reducing emissions and improving local air quality. Subway stations need to beautify the neighborhood. Buses are made to add union jobs. And every new transit project should reflect community input and empower residents. All of this impedes public transport’s ability to do its main job: transporting the public.

All these goals have merit. But each costs money and adds delay. The Transit Costs Project documents how the Boston Green Line extension, completed a decade later than anticipated, added a three-kilometer bike and pedestrian path after 13 people advocated for it at a community meeting, at a staggering cost of $20 million.

Every extraneous goal trades off against moving as many people as possible and against the welfare of the poor, who use transit the most. While 91.5 percent of American households own at least one car, less than half (45 percent) of transit riders have a vehicle available to them at home.

Buses are a rounding error as a proportion of vehicles on the road, accounting for less than one percent of US transportation emissions. Yet they operate under more rules and regulations than personal cars do. Governments build roads, highways, and parking structures with much more focus on their primary mandate: to improve mobility. But transit agencies answer to a far longer list of requirements.

Subscribe now

Transit side quests

Transit missions didn’t always creep. Until the middle of the twentieth century, almost all transit was privately owned, and the goals were simple: maximize ridership and fare revenue while minimizing costs. But starting in the 1910s, transit companies struggled because of competition from the car.

In the 1960s, governments began taking over languishing transit lines. This gave rise to a new problem: transit came to rely on taxpayer subsidies, with the majority of funding coming from voters who didn’t use it. Most of the public now drove, so the case for continued subsidy had to be made based on non-users’ interests. Public transit aligned itself with the growing social movements of the 1960s and 1970s: the War on Poverty, the Civil Rights Movement, environmentalism, and the oil crisis. Today, the American Public Transit Association touts public transportation as a cure-all: transit investments, it says, ‘will get Americans to work, to education, and to healthcare, and it will also get our nation to more job creation, less traffic congestion and cleaner air’.

The typical transit agency gets funding from federal, state, and local sources. Each level of government can add more goals. The federal government might require domestically sourced materials (such as Buy America), daycare for manufacturers (like the CHIPS Act), or a higher minimum wage for contractors and subcontractors (as is the case for Davis-Bacon prevailing wage rules). States might add extra environmental review (like the California Environmental Quality Act). And local governments can shape design, public art elements, local hiring, and the means of conducting community engagement.

The transit tradeoff

Alongside my co-authors, I studied six transportation pilot programs that were tasked with various goals, among them: reducing emissions, improving mobility equity, and reducing miles driven in cars. All of the pilots, which included electric carshare, bikeshare, and microtransit services, were funded by the California Air Resources Board and were located in disadvantaged areas across California.

By and large, these programs did improve the mobility of the badly off: most users lived in households earning under $25,000 a year, and many of the trips were necessary to get to work, school, or medical appointments. But the programs added 128,880 net new vehicle miles and slightly increased overall emissions rather than decreasing them. As mobility schemes, they worked, but on other margins they did not.

The problem is not just specific equity or environmental programs. Existing services are being eroded by attempts to make buses electric. Battery electric buses cost more to procure, and parts are more expensive to replace. Austin’s CapMetro 40-foot electric buses cost $917,000 apiece, whereas their diesel buses cost just $535,000. In south Florida, the Miami-Dade county’s transit agency spent approximately $1.1 million per electric bus. On any given day, out of the 75 buses it purchased, only about six are operating. That’s because the electric buses break down every 600 miles (seven times as often as their diesel equivalents), and because parts are difficult to come by, particularly since the manufacturer, Proterra, filed for bankruptcy.

In Germany, electrifying bus fleets increased costs by 12 percent. The problem is even worse in the United States because of Buy American rules. In Europe, where Chinese manufacturers compete freely, a standard 12-meter electric bus sells for roughly $600,000. US agencies pay nearly twice as much. While demand for electric buses is growing, the US market remains small, leaving agencies with few competitors to choose from. Out of roughly 63,000 buses in the US, approximately 7,000 are electric, 5,000 of which are school buses.

Moving from diesel to electric buses doesn’t just mean swapping vehicles: it also requires new software, land use permitting, grid connections for charging infrastructure, and worker time to fuel vehicles. Just routing electric buses around charging infrastructure adds significant complexity to operating the service.

Every dollar spent complying with Buy America or staging community meetings is a dollar not spent improving frequency or coverage. Assuming the median cost per hour for operating a bus in the US is $131, and that the median US bus carries 14.3 passengers per hour, the money for electrifying one bus could fund roughly 2,300 additional service hours, carrying at least 30,000 additional riders.

Prices make perfect

Electrifying transit is one way to reduce emissions, but it’s not the most efficient. Researchers studying Stockholm’s busiest bus route found that better pricing roads and transit, and running buses more often, yielded more benefit than just electrifying buses. From a passenger perspective, electric buses are no different. But operators lose out because costs rise by at least 16 percent, depending on the charging setup. Combining road charges with more frequent buses entices drivers to shift to transit, reducing emissions more substantially than electrifying a few buses.

When transit becomes more viable and reliable, we see a positive feedback loop. People who would otherwise drive opt for transit, which boosts revenue and feeds back into improved quality. On average, increasing transit service frequency by 1 percent boosts ridership by about 0.5 percent. Once buses arrive every ten minutes, bus services become more appealing for riders with alternatives. These switches are the only kind that can make a substantial dent in emissions.

Congestion pricing would reduce emissions much more effectively than electrifying buses. In the few places brave enough to try, the outcomes have been significant. In London, greenhouse gas emissions from vehicles fell by 16 percent, and the charge generated £227 million in a year. As well as this, traffic accidents fell almost immediately, with nine percent fewer accidents in the congestion charge’s first year.

It’s much easier, of course, to encourage transit ridership in places where people and destinations cluster together. Switching people from driving to transit saved nine million metric tons of carbon in 2018. But we can prevent 66 million metric tons of carbon emissions by decreasing the distances people need to travel through more efficient land use. When distances are short, walking, biking, and transit all become more appealing, and when people do drive, they drive shorter distances. In major cities, where transit is more dominant, electrifying buses makes more sense than it does in car-dominant places, like Fresno, California, where it’s more important to move low-income people to their jobs.

Focusing transit on what it does best

In most of the US, not having a car makes poverty worse. Poor people who gain access to a car are more likely to find jobs, keep their jobs, find higher paying jobs, work more hours, get off welfare, and move to better neighborhoods. Even beyond economic outcomes, people who don’t have cars take part in fewer activities outside the home, have fewer extracurricular activities and schools to choose from, fewer grocery store options, and are more likely to delay medical care.

Scope creep fails on its own terms. We are asking people already struggling to make ends meet, who already emit far less than most Americans do, to save the planet. But this is self defeating. Every dollar we spend on the environment or union jobs is a dollar we don’t spend on making transit more competitive against cars.

A 2018 UCLA report on transit ridership in Southern California estimated that if just one in every four people who rarely rides transit replaced a single driving trip with transit every two weeks, annual ridership would grow by 96 million. It’s more sensible to reduce emissions by getting a broader base to make small behavioral changes than to force a small group of already burdened people to carry the load.

Miriam Pinski is a researcher at the Shared-Use Mobility Center.

Subscribe now

Jacob Witten explains why siRNA will change medicine as we know it.

If you want a picture of biomedical research, imagine a boot stamping on a biologist’s face – for decades. The boot is labeled ‘medicinal chemistry’. This should not be taken as an insult to medicinal chemists, who heroically navigate maybe the hardest field in biomedicine.1 Rather, what I mean is this. A biologist might have a clear hypothesis about how to stop a disease, such as: blocking a particular protein will lower blood cholesterol and reduce the risk of heart disease. Naturally enough, the biologist would like to test that hypothesis. But there is no magic button to switch off this protein; something physical has to do the blocking. Usually, that thing is a small chemical carefully designed to be administered into the body, bind to the protein, block it – and do nothing else. In practice, this almost never goes as planned, which is a major reason most drugs fail in clinical trials.

It’s worse than this: medicinal chemists struggle to come up with ways to interact with most proteins at all. The majority of human proteins are considered ‘undruggable’, meaning that none of the small molecules we can currently synthesize can effectively bind to them, either because those proteins lack a convenient pocket for drugs to attach to or because they are ‘intrinsically disordered’, with little coherent structure.2 Drug discovery ends up focusing on the minority of targets that are druggable, like the proverbial drunk searching for his keys under the streetlamp because that’s where the light shines.

Even for those targets, success is far from guaranteed. A drug that works in the lab might be broken down in the body before it reaches its target protein, interfere with other proteins and cause toxic side effects, or fail to be absorbed and distributed to the right tissues. Our ability to predict what small molecule drugs will do in the body is so poor that even if the drug works, it might be for a different reason than originally hypothesized!3

But what if, instead of spending years optimizing small molecule chemistry to treat just one disease, and all that work merely delivering a sharp reminder that no plan survives first contact with the enemy, there really was a magic button to switch off any gene we chose? In that case, we could treat not just high cholesterol but dozens of deadly diseases, from Alzheimer’s to diabetes to Huntington’s disease.

Welcome to the world of siRNA therapy.

Silencing genes

The story of siRNA begins in 1990, when the scientists at the DNA Plant Technology Corporation in California were trying to figure out why their petunias turned white. They had actually been trying to make their petunias darker, by adding an extra copy of the gene for an enzyme that produces pigment. Presumably, adding an extra copy of a gene for an enzyme would mean more enzyme and therefore more pigment. But somehow, the extra copy eliminated the enzyme’s production, rather than boosting it. They named this baffling effect ‘cosuppression’. Subsequent work by other researchers revealed its cause: a special kind of RNA molecule, siRNA, had interfered with the enzyme’s production. Andrew Fire and Craig Mello later won a Nobel prize for this discovery.

Biologists had already known about RNA for several decades. Similar to DNA, RNA is a complex molecule built from a chain of smaller building blocks that encode genetic information. But the two differ in one important detail: the building blocks of RNA have one extra oxygen atom compared to DNA (hence its name, ribonucleic acid, as opposed to DNA’s ‘deoxy’-ribonucleic acid). This oxygen is prone to chemical reactions that can break RNA molecules. DNA is stabler and is therefore used to store genetic information in all multicellular life. RNA molecules tend to be short-lived, and take many different forms within cells, carrying instructions, helping to assemble proteins, regulating genes, and catalyzing reactions.4 And while DNA is ‘double-stranded’, with two linked strands of building blocks twisting into its famous helix shape, RNA often exists as just one strand.

DNA contains the instructions for making proteins, from the enzymes that digest food to the keratin and collagen that form our hair and skin. But to get from DNA to protein, the genetic code is first transcribed into an intermediate RNA molecule, called ‘messenger RNA’ or mRNA, which is then translated into protein. If the mRNA is destroyed, the protein won’t be built.

That’s exactly what siRNA, or ‘small interfering RNA’, does: it’s a short strand of RNA that interferes with the production of protein by destroying mRNA. An siRNA molecule binds to a piece of mRNA with a matching sequence, like a kind of barcode, and targets it for destruction by the cell’s gene-silencing machinery, which cuts the mRNA into pieces.

siRNA also explains what happened in the petunias. Adding an extra copy of the pigment-producing gene triggered the petunias to develop siRNA targeting that sequence, and because the newly introduced gene and the original gene shared the same sequence, both were silenced, the flowers lost their pigment and turned white. This is a naturally occurring process: siRNA is used to ‘silence’ unwanted genes, such as those of viruses that have entered the cell. But we can also use it to artificially block the production of proteins that cause disease.

Subscribe now

siRNA therapy

For some diseases, gene silencing has already succeeded. One example is hereditary transthyretin amyloidosis, a condition caused by a mutation in the transthyretin gene, which makes that protein misfold and clump together in the bloodstream, nerves, and heart. Over the years, the deposits build up, damaging nerves and stiffening the heart muscles, which can eventually lead to heart failure. Until recently, the condition meant a life expectancy roughly a decade shorter than average.5

In 2018, the FDA approved the very first RNA interference drug, called patisiran, to treat the nerve damage caused by this disease. A newer, longer-lasting version called vutrisiran was approved in 2022. Both drugs use siRNA to prevent the production of the misfolded protein so that clumps don’t form, which halts or slows down progression of the disease.

This approach could be adapted to many different diseases, from high cholesterol to Alzheimer’s, whose progression hinges on a small number of critical proteins. RNA interference makes it possible to target those proteins specifically and stop them from being produced.

Have a gene you’d like to silence? Identify the gene’s sequence, synthesize a short siRNA sequence to match it, deliver the siRNA into the right cells, and bam – instant knockdown. It sounds simple enough in theory, but that last step, getting siRNA into the right cells, has proven surprisingly difficult. Only after decades of grinding organic chemistry has it been solved.

The delivery problem

If you just injected siRNA into a patient’s veins, nothing useful would happen. There are at least three reasons for this. First, the body is full of enzymes that recognize and destroy unprotected RNA, including siRNA. Second, even a perfectly intact siRNA molecule would do nothing in the bloodstream, as it needs to get inside a cell to reach its target mRNA. Third, the way it would get into a cell involves being enveloped in a small bubble called an endosome, where it would be broken down by digestive enzymes. So an siRNA molecule would need to stay intact, enter its target cells, and then somehow escape from the endosome without being digested.

One way to solve these challenges is to use nature’s own delivery system: viruses. Viruses have spent billions of years evolving to get past our cells’ defences, find their way in, and release their proteins. So what if we used viruses to carry siRNA into our cells? Researchers have tried to do just that, by engineering harmless viruses to carry and deliver siRNA into specific tissues, including the brain. But viruses come with a drawback: just as they have evolved to infiltrate our cells, our immune systems have spent hundreds of millions of years learning to recognize and destroy them. Even carefully designed viral delivery systems can trigger immune reactions, especially if they’re used repeatedly, which can be risky for patients and make treatments less effective.

Signed, sealed, delivered

Another approach has focused on packaging RNA inside tiny fat-like particles, called liposomes, to protect and help it enter cells. Liposomes were first explored in the 1960s, and could shield RNA from being broken down in the body to some degree. But liposomes were far less successful at entering cells, because they bound only weakly to their outer membranes, and were even worse at escaping endosomes and releasing their payload of siRNA into the cells.

That challenge was overcome in the 1980s, when researchers tweaked liposomes to bind more tightly to negatively charged cell membranes, by incorporating lipids with a positive electric charge. While this helped get the RNA into cells, it came at a cost: the strong positive charge made them interact with cell membranes too strongly and damage them.

The next breakthrough was more subtle. Instead of using lipids that were always charged, researchers incorporated lipids that could change their charge depending on the acidity of their environment, called ‘ionizable lipids’. These lipids are neutral in the bloodstream, minimizing damage, but turn positive once inside an endosome, as endosomes are acidic. This destabilizes the endosome’s membrane, releasing the siRNA into the cell.

Even after coming up with that basic idea, the problem was nowhere near solved. It took more than a decade of tinkering with ionizable lipid chemistry, leading to a thousand-fold improvement in potency, to produce lipid nanoparticles that performed all these three steps of delivery (stability, uptake into cells, and endosomal escape) safely and efficiently.6

Patisiran, the first FDA-approved siRNA drug, was the first success that took this approach, by delivering siRNA in ionizable lipid nanoparticles to silence the mutated transthyretin gene in liver cells and slow the progression of amyloidosis. It was proof that siRNA could be turned into a real medicine. But it also arrived, ironically, just as the use of lipid nanoparticles for siRNA was being eclipsed by a more efficient method.7 What if siRNA didn’t need a carrier at all?

Naked siRNA

So far, researchers had focused on shielding siRNA from being broken down inside the body. But then they tried a new tack: making the siRNA molecule itself sturdier so that it could survive unclothed.

To understand how this was possible, let’s return to the difference between DNA and RNA. RNA has an extra oxygen atom, which makes it vulnerable to reactions that break it apart. By chemically modifying that pesky oxygen – for example, by swapping the oxygen for less reactive fluorine or hydrogen, or linking a methyl group (a highly stable formulation of one carbon atom and three hydrogen atoms) to it – the RNA molecule can be made much more durable. These small, precise chemical changes allowed Alnylam Pharmaceuticals (which also developed patisiran) to create siRNA molecules with almost indefinite protection against degradation when injected naked.

With stability solved, the next challenge was guiding this naked siRNA to its target. The siRNA drugs carried by lipid nanoparticles naturally accumulated in the liver, because lipid nanoparticles impersonate cholesterols which get processed there. This made the liver an easy target for siRNA drugs. But without lipid nanoparticles, naked siRNA molecules wouldn’t concentrate at a target organ. So researchers attached a sort of address label to get them there: three copies of a small sugar molecule called GalNAc. Liver cells have receptors for GalNAc on their surfaces, which recognize the sugar and bring it inside their endosomes. This directed siRNA to its intended destination.

Alnylam had cracked the first two hurdles of delivering naked siRNA drugs: it had created siRNA that did not instantly break down in the bloodstream, got to the cells it needed to, and entered them. That left the final hurdle of escaping the endosome. Without ionizable lipids to break the endosome membrane, how would naked siRNA ever make it out of endosomes and into the interior of the cell? The answer turned out to be unexpectedly simple. While most naked siRNA remains confined in the endosome, a small proportion slips out through some fluke occurrence, and more continues to be released over time. The proportion of siRNA leaking out of endosomes can be well under one percent, but often that is enough because siRNA is so potent – very little of it is actually needed to have its gene-silencing effect.

The result is a massive difference in how long the drug lasts. Patisiran, which is carried by a lipid nanoparticle, needed to be dosed every three weeks. In contrast, Alnylam’s newer drug, vutrisiran, a naked siRNA drug attached to a GalNAc sugar, is approved to treat the same medical condition, but needs to be dosed only once every three months. Other drugs based on naked siRNA and GalNAc now exist that only need to be topped up every six months. GalNAc siRNA drugs also have another advantage. Patisiran, with its lipid nanoparticle, carried the risk of triggering immune reactions, so patients had to be given immunosuppressants alongside it; but this precaution is unnecessary for those attached to GalNAc.

Simply put, temporarily switching off a precise gene in the liver is now a solved problem, and it can be achieved with drugs that require no more than four administrations per year. Multiple siRNA drugs have been approved for treating liver diseases, both rare and common, including treatments for hereditary transthyretin amyloidosis, hemophilia, high cholesterol, and acute hepatic porphyria, a nasty lifelong condition that causes attacks of pain, vomiting, and breathlessness because of a faulty enzyme. Many more siRNA drugs are in late-stage trials, including treatments for high blood pressure, diabetes, and fatty liver disease.

Subscribe now

Beyond the liver

Every success story so far has involved the liver. But of course the liver is not the only organ in the body. The reason the liver dominates the story is not that siRNA will work only there but that the liver was an easy starting point. But once that approach worked, it suggested a broader idea – if siRNA can be stabilized and delivered by attaching a molecular ‘address’ to it, then in principle, different labels could be used to guide it to different organs.

That’s exactly what the field is now trying to do. By swapping out the sugar used to target the liver for other molecules, researchers are developing drugs targeted for other organs, including the kidneys, lungs, fat tissue, muscle, and brain. The competition is intense, and if any company stumbles, many other hungry startups, like Manifold Bio and Soufflé Therapeutics, will be hot on its tail.

Among these efforts, the highest-stakes trials are those aimed at the brain. They target one of modern medicine’s bêtes noires: Alzheimer’s disease. The most influential theory of Alzheimer’s, though it remains controversial, is that the disease is driven by a misfolded protein, amyloid beta, which is produced from a larger amyloid precursor protein. According to the theory, these misfolded proteins accumulate into clumps that trigger the accumulation of another protein, tau, which causes a loss of neurons and cognitive decline. This hypothesis naturally suggests two obvious intervention points: either reduce the production of amyloid precursor protein upstream or the production of tau downstream. Alnylam’s program targets the amyloid precursor, while Arrowhead’s targets tau.

These drugs will face different challenges than earlier siRNA drugs, which targeted the liver. The most immediate is accessing the brain, which is protected by the blood-brain barrier, a tight layer that seals and defends the brain from most molecules in the bloodstream. Alnylam’s current strategy is to bypass this barrier by injecting the siRNA directly into spinal fluid by ‘intrathecal injection’, where a needle inserted into the spine delivers drugs directly into spinal fluid, like in an epidural. Their siRNA is also attached to a fatty acid chain, which they believe will successfully deliver it to the relevant brain cells. But while this approach might prove effective, it’s also uncomfortable for patients and not ideal for frequent dosing.

Arrowhead is trying the bolder approach of delivering siRNA by injection under the skin, using a proprietary targeted siRNA molecule that’s meant to cross the blood-brain barrier itself. There’s a precedent for this approach, but no guarantee it will succeed.

Even if the amyloid hypothesis is correct and delivery succeeds, biology might still limit what siRNA can achieve. Famously, by the time Alzheimer’s disease is diagnosed, the damage to the brain is often extensive enough that clearing amyloid plaques has little effect on slowing its progress. Whether targeting tau might be more effective at later stages remains an open question. Yet the broader point still stands: siRNA delivery beyond the liver is a matter of when, not if. If biologists can identify proteins that are critical to the progression of a disease, those diseases can become treatable or preventable.

The future of programmable medicines

siRNA falls into the category of therapies we could call ‘programmable medicines’. Once medicinal chemists have worked out how to get a programmable medicine into a particular organ, all that’s required to treat a new disease of that organ is to specify a new RNA or DNA sequence while holding the chemistry constant.8 9 So vutrisiran, the siRNA treatment for hereditary transthyretin amyloidosis, works according to the exact same principles as inclisiran, the siRNA that targets PCSK9 to reduce cholesterol levels.

siRNA is not the only programmable medicine in use, and other platforms have capabilities that siRNA lacks. For example, antisense oligonucleotides (ASOs) are short strands of synthetic genetic material that can alter RNA and be delivered similarly to siRNA. One such ASO, targeting the tau protein involved in Alzheimer’s disease, has shown promising results in a phase two clinical trial. mRNA vaccines can trigger the production of certain proteins in our cells, and are a blindingly fast way to develop effective vaccines against viruses, as we saw during the Covid pandemic. CRISPR-based gene editing can permanently fix genes, rather than just temporarily switching them off, by directly altering cells’ DNA.10 The common thread is that all these approaches link biological understanding directly to medicine. Once delivery is solved, the medicinal chemistry boot is off the biologist’s face, and they can test new treatments simply by switching out the target genetic sequence.

Each of these forms of programmable medicine has already produced FDA-approved treatments. So far, only one class of problems has been solved by programmable medicine: gene silencing in the liver by siRNA. But sooner or later, the same will be true of other organs. As scientists solve each delivery problem, we’ll experience an explosion of safe, convenient treatments against a myriad of diseases that were once considered untreatable. Soon, they will simply be waiting their turn.

Jacob Witten is a professor at Case Western Reserve University.

Subscribe now

Derek Hopper explains why Thailand was one of the only countries not to be colonized.

At the beginning of the 1833 dry season, a monk named Mongkut set out for Sukhothai, the old capital of Siam. Long journeys by boat and on foot for study, teaching, and religious observance were common for monks like Mongkut. Theravada Buddhism was a huge part of life in premodern Siam, and at any given time, a small percentage of adult men were ordained as monks. As they traveled around the kingdom, locals provided them with food, clothes, and lodging.

But Mongkut was no ordinary monk. He was the 43rd child of King Rama II. Born to one of Rama II’s senior consorts, he was a high-ranking son and in the running to inherit the throne. As such, he would have been traveling with a retinue of attendants as well as fellow monks. The kingdom to which Mongkut was an heir covered most of modern-day Thailand, plus parts of Laos, Cambodia, and Malaysia, and contained around five million subjects. Though most of these subjects were poor rice farmers, Siam’s largest city, Bangkok, was a major trading port, with a dense network of canals lined with houses on stilts, and an ethnically diverse population.

In contrast to the bustling capital, Sukhothai was by this time largely abandoned. From the thirteenth to fifteenth centuries, Sukhothai had flourished as a political, cultural, and religious center, but it had since been eclipsed by Ayutthaya to the south and, since its founding in the eighteenth century, Bangkok. When Mongkut arrived there, he would have been greeted, as visitors are today, by crumbling stupas (religious buildings), serene Buddha statues, and rust-colored brickwork weathered by centuries of blistering sunshine and tropical rains.

At some point during his stay, Mongkut came across a remarkable object: a four-sided, black stone monolith, about a meter high and inscribed with an unusual script. The stone would become known as the Ramkhamhaeng Stele. Purported to date from 1292, it is often cited as the oldest surviving example of Thai writing.

Mongkut brought the Stele to Bangkok and assembled a committee of scholars to decipher its enigmatic inscription. They compared it to known forms of old Thai and other related scripts, analyzed linguistic patterns, and collaborated with learned monks to interpret unfamiliar words and characters. What they found was extraordinary: the 124 lines of archaic text told of an ancient Thai kingdom ruled by a wise monarch, Ramkhamhaeng. According to the Stele, Ramkhamhaeng’s kingdom combined a literary tradition, a sophisticated legal and political system, independence, sovereignty, secure geographic boundaries, Buddhist kingship, and just rule.

The discovery of the Stele was, as it turned out, serendipitous. Over five centuries, European powers colonized virtually every other territory on Earth, with exceptions that can be counted on the fingers of one hand. Japan is the best known example. Siam, perhaps the next clearest case of a state that resisted foreign occupation and retained sovereignty, is much less publicized. Siam held out through a combination of diplomacy, reform, and careful image management. By providing evidence of a longstanding complex civilization, the Ramkhamhaeng Stele was just the sort of brand asset the kingdom needed.

The Siamese Holdout

By the 1830s, the Siamese court was watching nervously as British power radiated outward from India. Just a few years before Mongkut’s discovery, during the First Burmese War of 1824–1826, British gunboats sailed up the sacred waters of the Irrawaddy River and humiliated the ancient kingdom of Burma, extracting huge territorial concessions from Siam’s long-term rival. To the east, French missionaries were active in Vietnam and Cambodia, representing the earliest phase of France’s colonial ambitions and its mission civilisatrice. One by one, Siam’s neighbors began to fall and it found itself the sole Southeast Asian holdout against European colonialism.

The vanquished countries pursued a range of resistance strategies, all of them unsuccessful. Burma fought a series of doomed wars against Britain, only to be annexed. Cambodia willingly allowed itself to become a French protectorate, viewing this as the lesser of several evils after decades of encroachment from neighboring Siam and Vietnam, only for that protection to evolve into colonial rule within French Indochina. Vietnam relied on the country’s historic ties to China to ward off France, but its harsh treatment of missionaries and minorities gave Europeans an easy pretext for intervention.

Instead, Siam’s leaders hoped that demonstrating it already had clear markers of civilization would undermine the pretexts for colonization. Even in the nineteenth century, countries did not want to be thought of as engaging in naked land grabs. Successful colonial ventures usually combined ostensibly noble justifications and straightforward power-hungry motivations. Europeans believed that technologically advanced, Christian nations had a moral duty to bring progress to ‘backward’ peoples who lacked proper government, writing systems, and cultural refinement. This ideology created domestic political support and international legitimacy for territorial conquest.

Mongkut’s discovery of the Stele was comparable to finding a lost Magna Carta at just the right moment. Siam’s rulers realized that written language was key to civilizational legitimacy in Western eyes, and the inscription provided exactly what they needed: tangible evidence of a tradition of literary sophistication that overturned European assumptions of primitiveness.

Diplomacy

In 1855, a new British special envoy to Southeast Asia arrived in Bangkok. Sir John Bowring was governor of recently conquered Hong Kong and represented a nation at the height of its powers. By this point, Britain controlled almost a fifth of the world’s land mass, produced over half its industrial output, and had the most powerful navy the world had ever seen. Siam, on the other hand, had been in self-imposed relative isolation from the West since 1688, and had recently been accused of dealing contemptuously with British and American trade missions. John Crawfurd, a British envoy, described the Siamese as ‘unusually sordid, insincere and rapacious’. Under Rama III, Siam’s king and Mongkut’s older half-brother, most people thought Siam was headed down the same path as its neighbors.

After Rama III died in 1851, Mongkut was crowned king, taking the name Rama IV. Mongkut was popular with the British, who thought him more friendly to their interests than the other contenders for the throne. As a monk, he had studied Western languages, sciences, and technology. He spoke English and Latin and had continuous contact with diplomats and Catholic and Protestant missionaries. He was fascinated by the Western concept of material and technological progress, an idea in stark contrast to Buddhist cosmology’s emphasis on repeated cycles of decay.

European diplomats had often found Asian rulers, including Mongkut’s predecessors, to be aloof and disdainful. Arriving in Siam for his meeting with the new king, Bowring would have expected more of the same. Instead, he found a ruler who displayed a sophisticated understanding of the Western world. King Mongkut received Bowring in his private apartments for cigars and wine. They bypassed interpreters and spoke in English. Bowring noted that the king’s library had a vast array of books ranging from Western science to novels by Sir Walter Scott.

British imperialists were unaccustomed to negotiating with Asian rulers who could meet them on their own intellectual ground. This was an era in which Thomas Macaulay, the colonial administrator and historian best known for his History of England, could write that ‘a single shelf of a good European library was worth the whole native literature of India and Arabia’. Bowring, however, was willing to believe the Siamese were cultured. His influential 1857 work, The Kingdom and People of Siam, featured the Ramkhamhaeng Stele, recognizing it as a major historical document that provided evidence of early Thai writing and was crucial to understanding Sukhothai’s sophisticated governance and society.

The treaty that Mongkut and Bowring negotiated was a decisive shift in the relationship between Britain and Siam. Three decades earlier, in 1826, a treaty had opened limited trade between the two countries. The 1855 treaty was by no means generous. It capped Siamese import and export duties at 3 percent and gave significant extraterritorial rights to British subjects, meaning Britons could not be tried in Siamese courts. But the treaty massively increased foreign trade, and crucially, Siam continued to be treated as a sovereign negotiating partner.

The contrast with other countries in the region is stark. Following its defeats in the Anglo-Burmese Wars of 1824–26 and 1852, Burma had been forced to surrender four provinces, pay a crippling £1 million indemnity (about $160 million today), and accept the presence of a British overseer with veto power over the king’s decisions. Similarly, China’s attempt to enforce a ban on Britain’s opium trade in 1839 had resulted in the loss of Hong Kong and the start of what nationalists would later dub the ‘century of humiliation’. Mongkut demonstrated what strategic compromise could achieve when resistance failed.

Xenophilia

Siam’s distinctive approach was not as simple as a cigar-smoking bibliophile king. That was a small part of a broader strategic performance of European norms, an attitude that set Siam apart from other countries in the region.

In response to Britain’s first embassy to China in 1793, Emperor Qianlong dismissed Western technology, declaring that the Middle Kingdom ‘possesses all things in prolific abundance’ and had no need for the goods of ‘barbarian merchants’. Chinese rulers were trained in classical Confucian thought that emphasized China’s cultural superiority, and their insularity and xenophobia made it easy for Europeans to justify their civilizing missions. Similarly, Vietnam’s Emperor Minh Mang rejected French overtures in the 1820s and 1830s. Vietnam’s isolation would later provide France with the pretext for intervention. Both rulers were products of educational systems that viewed foreign knowledge as contaminating rather than useful.

When Asian rulers did embrace modernization, they often did so reactively, after the West had already put them under substantial pressure. Despite having ancient scripts dating back to the sixth century, magnificent Buddhist temples, and sophisticated legal traditions, Burma was systematically dismantled by Britain between 1824 and 1885. The crucial differences between Burma and Siam were timing and agency. Burma was first invaded in 1824, before the ‘civilizing mission’ ideology was in full swing. King Mindon, who ruled Burma from 1853 to 1878, modernized extensively after Britain’s initial conquest, establishing telegraph lines, railways, and modern schools. Yet by then, Britain had generated military and political momentum that rendered Burma’s cultural credentials and reforms irrelevant. When Britain manufactured border disputes to complete Burma’s annexation in 1885, Mindon’s modernization efforts provided no protection against a colonial power that was, by that point, committed to conquest.

Japan also modernized reactively after the US Navy’s ‘black ships’, under Commodore Matthew Perry, forcibly ended the Tokugawa Shogunate’s policy of isolation in 1853. China attempted to do something similar following the humiliation of the Second Opium War, though with much less success. In comparison to its neighbors, Siam strategically adopted and demonstrated the markers of civilization that European powers used to justify colonization elsewhere from a position of relative strength.

In 1868, Mongkut extended invitations to British and French officials to observe a solar eclipse. This was a grand affair with pavilions and accommodation prepared for the attendees, the goal of which was to showcase Mongkut’s commitment to science. Mongkut accurately predicted the timing and location of the eclipse using a combination of traditional Thai timekeeping methods and Western astronomical techniques. According to some stories, his calculations were so precise that they trumped those of the French astronomers present.

The Siamese court knew what to perform to whom. France had long considered science to be the true marker of civilization, while Britain championed international law and free trade. Mongkut demonstrated Siamese civilization through measures that European powers used to justify colonization elsewhere.

Creating brand Siam

Mongkut did not live to see his diplomacy come to fruition: he contracted malaria at the eclipse event and died a few weeks later. His son Chulalongkorn (Rama V) was a minor at the time of his father’s death, but assumed full control of Siam in 1873, finding himself at the head of a multinational, decentralized, and dynastic kingdom.

Across Europe and its empires, traditional monarchies were adapting to an age of nationalism by imposing unified national identities from above. France had established a centralized administrative system with uniform laws, and aggressively promoted Parisian French as the national language, systematically suppressing regional languages like Breton, Occitan, and Alsatian. Meanwhile, Britain more gradually imposed standard English through education reforms and civil service requirements, displacing Welsh and Gaelic. The Austro-Hungarian Empire was, in its Magyarization policy of the 1880s, doing the same: imposing Hungarian language and culture on ethnic minorities like Slovaks, Romanians, and Croats to create a single national identity in the Hungarian part of the dual monarchy. Germany and Italy both transformed from complex patchworks of states to unified nations in the late nineteenth century.

Despite Europeans having only recently created their centralized nation states, this became the new standard for civilization. Many Asian powers lacked the cultural homogeneity, clear boundaries, and single language and government that nineteenth-century Europeans considered civilized. And these diverse and decentralized realms were ripe for divide-and-rule tactics. The British and French depicted non-dominant groups in realms like Burma, Cambodia, and Vietnam as oppressed minorities in need of their protection.

Nineteenth-century Siam was, in theory, vulnerable to the same tactics. It encompassed dozens of ethnic groups and lacked a unified Thai identity. Its people were governed by the mandala system, the traditional premodern governing system in Southeast Asia, its equivalent to Europe’s feudal system. Under the mandala system, rather than fixed borders, the king’s sovereignty faded with distance, with outer parts of the kingdom recognizing overlapping zones of authority from elsewhere.

When the British became neighbors to Siam’s south and west in the 1820s by acquiring the Straits Settlements and annexing lower Burma, their request to demarcate fixed mutual borders baffled the Siamese. European powers, once they understood the system, would attempt to exploit this difference in understanding. The French seized on Siam’s multiethnic structure, arguing that the Lao constituted a distinct race deserving protection from Siamese domination. They also claimed that the Siamese were not a true race, because they had become too intermixed with the Chinese.

Instead of giving in, Siam adapted through a program of nation-building. Chulalongkorn promoted the idea of ‘Thai-ness’, a single national identity that could accommodate Siam’s dozens of ethnic groups while presenting as a unified state to the Western powers. When confronted with French claims about distinct ethnic groups, Chulalongkorn countered: ‘The Thai, the Lao, and the Shan all consider themselves peoples of the same race. They all respect me as their supreme sovereign, the protector of their wellbeing.’

As well as a shared national identity, the people of Siam needed a shared language and clearly defined borders. The Bangkok dialect was elevated to ‘standard Thai’ and was spread through a newly created school system. The mandala system was dismantled in favor of a centralized bureaucracy, reorganized into administrative units that drew inspiration from the old mandala circles but imposed newly fixed territorial control. Modern mapping projects helped draw borders with unprecedented accuracy. A national census counted subjects who, a few decades later, were required to adopt surnames. Telegraph lines and railways created communication infrastructure that solidified Bangkok’s authority.

This approach differed dramatically from that taken by Vietnam. While Vietnam had a coherent identity dating back centuries, the ruling Nguyen dynasty struggled with adapting it to the Western concept of nationhood. Emperor Tu Duc was resolutely committed to maintaining Vietnam’s traditional Confucian order, and rejected reform. Vietnam retained a hierarchical system that privileged ethnic Vietnamese while marginalizing minorities such as the Cham and Khmer. The French capitalized on these self-imposed divisions by governing different regions separately – Cochinchina as a colony, and Annam and Tonkin as protectorates – thereby deepening regional fragmentation. The end result was an effective dismantling of the Vietnamese state.

By embracing the Western concept of nationhood, Chulalongkorn was able to force Europeans to recognize Siam as a sovereign country, rather than as a wilderness in need of conquest. Chulalongkorn embarked on grand tours of Europe in 1897 and 1907, amid sustained British and French pressure on Siam’s borders. Across Europe, he insisted on being received as a monarch of equal rank to his hosts. His entourage wore Western clothing, observed European court customs, and spoke fluent English. Some of his sons, including future Siamese kings, attended elite institutions such as Eton. The message was clear: Siam was a peer.

Modernizing Siam

As well as promoting the idea of a unitary Thai identity, Chulalongkorn took up a comprehensive program of modernization and centralization. In 1885, Chulalongkorn established the first modern public school. He created the Ministry of Education in 1892. By the end of the 1890s, the kingdom had about a hundred schools teaching a standardized curriculum, including the elite Suankularb Wittayalai school that trained future government officials in both Thai tradition and Western knowledge. It is still one of Thailand’s most prestigious secondary schools.

The legal system was also up for reform. The relatively unequal treaties imposed by Britain and France had granted extraterritoriality to European subjects, exempting them from Siamese law in a humiliating denial of sovereignty. Chulalongkorn’s solution was to create a legal system that Europeans would recognize as legitimate. He assembled a team of foreign advisors, most notably the Belgian jurist Gustave Rolin-Jaequemyns, who became a key architect not only of Siam’s new civil law code but of its entire diplomatic strategy. The choice of a Belgian was strategic: adjacent to British and French legal traditions but crucially not from either colonial power. Chulalongkorn built modern law courts and staffed them with the burgeoning administrative class trained in Siam’s schools. By demonstrating that Siam possessed a ‘civilized’ legal system, Chulalongkorn could argue for the abolition of extraterritorial privileges.

Chulalongkorn also Westernized the military. He hired German advisors and sent some royals to the Prussian military academy. In line with the Prussian model, military command was centralized under the monarch, noble levies were replaced with a standing army, and a professional officer corps was established.

Religion, too, was reformed to appear more rational by Western standards. Chulalongkorn supported the Thammayut monastic order’s reformation that made Siamese Buddhism appear less superstitious and more disciplined and text based. Even time itself was standardized. The kingdom adopted the Gregorian calendar and aligned its timekeeping with international norms. The quantification and standardization of time was foundational to Western modernity. Mechanical clocks, synchronized schedules, and precise measurement undergirded capitalism, science, and bureaucratic efficiency.

Cultural transformation reached into daily life through the promotion of siwilai, a Thai loan of the word ‘civilized’ that became central to the kingdom’s modernization program. Western-style clothing became increasingly common, often through official encouragement. Practices deemed uncivilized by European observers, such as chewing betel nut, were discouraged.

Perhaps most significantly for Western audiences, Chulalongkorn abolished slavery. Before the modernizations, Siam had a complex hierarchy of debt bondage, war captives, and corvée labor. By the late nineteenth century, slavery had been abolished in most of Europe and the Americas. Thailand followed suit. An 1874 decree freed children born into slavery when they reached the age of 21. It was followed by an 1884 ban on capturing and selling ethnic minorities into slavery. The 1905 Slavery Abolition Act went further, dismantling most remaining slavery and reforming debt bondage by crediting laborers’ work toward their principal debt rather than merely as interest. By 1908, slavery was criminalized and the government had a program of education to prevent former slaves from falling back into servitude.

In 1907, the French newspaper Le Figaro congratulated the king for his successful pursuit of modernization. It drew parallels between Siam and Japan, suggesting that France may now develop a beneficial relationship with an independent Siam. The same newspaper reminded readers: ‘one must not forget that the king of Siam, though his state is Asian, is a king of dignity like that of the Europeans.’

Soft power meets hard power

Siam’s strategy was tested during the Paknam incident in 1893. French gunboats forced their way up the Chao Phraya River toward Bangkok. Officially, the Paknam incident centered on a dispute between the Siamese and French regarding territory east of the Mekong River. In truth, it was prompted by France’s growing colonial ambitions following its conquest of Vietnam.

On 13th July, three French warships attempted to force passage past Siamese fortifications. The Siamese fired upon the warships. The French fired back, killing three sailors and breaking through the Siamese defenses. The French proceeded upriver towards the capital. They demanded that Siam recognize French Indochina’s claim to the disputed territory. In the face of overwhelming military force, Chulalongkorn ceded the territory, making a necessary concession to preserve the kingdom as a whole. Siam was forced to cede territory to the French in what is now Laos and Cambodia, creating much of the modern borders of Thailand. The French established a demilitarized zone along the Mekong, and the Siamese had to pay an indemnity of three million francs. European powers readily resorted to gunboat diplomacy but even here, France felt compelled to frame its demands in terms of legitimate Vietnamese territorial claims rather than naked conquest.

Between 1893 and 1909, Siam would cede around 40 percent of its territory to France and Britain. But the strategic retreat meant Chulalongkorn preserved what mattered most: the political independence of Siam’s core territories. The lost lands, predominantly Lao and Khmer-majority regions along the Mekong, had always existed at the outer edges of the mandala system, where Bangkok’s authority was weakest. Chulalongkorn specifically prioritized the Chao Phraya valley, the Thai-majority heartland, which was the source of the kingdom’s agricultural wealth and political identity. By surrendering territories where their control was already tenuous, the Siamese leadership prevented France from advancing into this core.

Siamese Wins

Some modern historians, many of them Thai, have questioned the authenticity of the Ramkhamhaeng Stele, suggesting that it may have been modified or fabricated to serve Siam’s existential myth-making needs. The Stele’s discovery mirrors other nationalist discoveries of the era, such as the Nibelungenlied, a medieval epic poem that German intellectuals promoted as a symbol of Germanic heroism and unity.

Whether Mongkut’s discovery was a true ancient artifact or a recent creation matters less than what Siam did with it. By the time French gunboats pointed their cannons at the Grand Palace in 1893, Siam had successfully established itself as a civilized nation worthy of sovereignty. The painful territorial concessions it made were closer to concessions European countries were in the habit of extracting from each other. It was not the kind of conquest that Europeans were doing in the New World, Africa, or the rest of Asia.

The kingdom that emerged from the colonial crucible bore little resemblance to the decentralized mandala system that had puzzled British border commissioners in the 1820s. It had become a Western-style nation. The ruling family of Siam had imposed one dialect across the populace, created a centralized state with the capacity to measure and monitor its people, standardized education, built infrastructure, and abolished slavery. They even created a national myth.

Yet rather than becoming Westernized by conquest, this transformation was carefully orchestrated from within. Mongkut and his son Chulalongkorn weren’t to know this, but their strategy may have eventually protected Thailand from a great deal of suffering. Weak institutions built by colonists fell apart after twentieth-century decolonizations, contributing to the deaths of millions of people across Cambodia, Vietnam, Malaysia, and Burma.

Siam demonstrated that a nation could transform itself on its own terms while others around it lost their chance.​​​​​​​​​​​​​​​​ The monk prince who discovered that stone in Sukhothai, armed with his synthesis of traditional Buddhist and Western scholarship, established a template for survival that would serve his kingdom for generations.

Derek Hopper is a writer and university lecturer based in Qatar.

Subscribe now

Does daycare damage children’s brains? So say a growing number of commentators, particularly on the political right. Prominent daycare critic Mikhaila Fuller, daughter of Jordan Peterson, explained to her 1.3 million podcast followers that it affects children in ‘pretty nasty ways’, warning them against ‘traumatizing’ their children. Erica Komisar, an American psychoanalyst, claimed in 2025 on the popular podcast Diary of a CEO that daycare makes young children more likely to ‘develop pathological defenses’ in response to the ‘trauma’ of being separated from their parents. ‘It’s so bad for their brain,’ she continued, ‘and it’s been known to increase aggression.’

At the same time, the educational establishment views daycare as not only indispensable to child development, but also a solution to problems like inequality and violent crime. The European Commission says that preschool ‘lays the foundations for later success in life’. The World Bank claims that it can ‘help countries be more productive, and compete more successfully in a rapidly changing global economy.’ Governments around the world spend billions of dollars on daycare, notionally as an investment in future members of the workforce.

Who is right? Does daycare traumatize children or does it turn them into upstanding citizens? Or perhaps both are true, and daycare sacrifices the emotional health of toddlers in order to turn them into subdued salarymen.

Although the confidence with which they are made might suggest otherwise, there is little evidence to support such extreme claims on either side. It appears that whether a child attends daycare usually makes little difference to their outcomes.

Stress testing

Daycare skeptics like Komisar point out that levels of cortisol, colloquially known as the stress hormone, are raised in children at daycare. This may be true. Children in daycare have higher cortisol levels in their saliva and their cortisol levels seem to rise throughout the day. But this needs to be understood in context. Cortisol isn’t innately bad: it plays an important role in regulating metabolism and sleep-wake cycles. Without any cortisol in your body, you would die. Even in an unstressed person, cortisol levels fluctuate: peaking when waking up in the morning, before declining over the course of the day, with short-term spikes in response to things like exercise and socializing. And the relationship between cortisol and the experience of stress is not well understood. For instance, cortisol levels can be lower in people who report that they are chronically stressed. While higher cortisol levels at daycare could indicate that children are stressed, it could also mean they are excited or stimulated by novelty and social complexity.

Cortisol levels can change by an order of magnitude over the course of a day, which means it is easy to get completely different results for the same person from one day to the next. This, as well as variation by age and factors like how recently children have exercised or eaten, means that reliable data is hard to obtain. The studies we have may not be well powered enough to detect a genuine signal amid the noise.

We don’t need salivary cortisol to know that some children find daycare stressful. Perhaps they prefer to be with their parents or find the busy environment overstimulating. However, this is vastly different from the claim that daycare is traumatic and will permanently stunt a child’s emotional development.

On the Diary of a CEO podcast, Komisar went even further and suggested that the stress of being separated from their parents causes the amygdala, a small part of the brain involved in emotion, of daycare-attending children to ‘become active precociously’. The amygdala then supposedly ‘shrivels up and burns out because it cannot manage that stress so early’, leading to chronic anxiety, depression, and ADHD.

This is pure speculation. No one has done the research to make a claim like this. We don’t even know whether people with smaller amygdalas have them in response to trauma or if they are born like that. Komisar’s ideas may sound fringe, but she is a mainstream parenting commentator, with contributions to newspapers like The Wall Street Journal and television shows like Good Morning America.

Too good to be true

Anti-daycare commentators aren’t the only ones making overblown claims about its effects. Many politicians and policymakers confidently state that daycare is a panacea for all manner of social ills.

In 2013, then-President Barack Obama said that every dollar spent on childcare gives a seven-dollar return, which, if true, would be extraordinarily high, higher than most transport infrastructure and comparable to the gains from providing clean water in developing countries. Obama claimed that this effect is thanks to daycare ‘boosting graduation rates, reducing teen pregnancy, [and] even reducing violent crime’, and that attending daycare can cause children to ‘form more stable families of their own’. Hillary Clinton has said that ‘the evidence is overwhelming’ that spending on daycare ‘is good for economic development’. Joe Biden advocated for universal preschool to give America ‘the best-educated workforce’ in the world. Former New York mayor Bill de Blasio said that universal preschool would create ‘a more fair and just society’. Similarly, the British government has claimed that its recent expansion of subsidized daycare to nine-month-old babies will help them to ‘achieve better in school’ and promote their ‘future success [...] on the labour market’.

If these claims were true, daycare really would be a miracle intervention. But is it? Some of the most influential data on this topic comes from moderately sized observational studies commissioned in the 1990s and 2000s in Britain and the United States. These tested children’s academic and social skills at preschool age and later as they progressed into elementary school, finding that children who attended high-quality preschools performed slightly better on literacy and numeracy tests. But this early boost seems to fade by a few years into elementary school. The evidence is even more mixed on potential improvements to children’s social skills, with some studies finding children who attend daycare are slightly better at cooperating, while others find they have slightly more behavioral problems.

The clearest benefit is for children from disadvantaged backgrounds, which means children living with some combination of poverty, low parental education, single parenthood, or family instability such as foster care. Two famous studies (the Perry Project and the Abecedarian Project) from the 1960s and 1970s investigated the effects of intensive, targeted interventions for black children from especially deprived families living in segregated America. Researchers reported that children in these programs later had higher earnings and lower arrest rates. (The Perry Project was cited as evidence for Obama’s seven dollar claim.)

But both of these studies looked at children in very particular circumstances, who received not just ordinary daycare but intensive support that included free healthcare and home visits. Although the studies were randomized, they had small sample sizes of roughly a hundred children each, and their statistical methods were imperfect by modern standards. To suggest that universal daycare will deliver similar results in America today is, to put it generously, an audacious extrapolation.

Studies on daycare are usually observational rather than experimental. It is hard to randomize how children are looked after, which means it is hard to say whether effects are caused by childcare itself or by something else that is different about families that use it. One rare exception is a randomized controlled study from Tennessee in the 2000s, which investigated ordinary preschool education and followed children as far as high school. It reached similar conclusions to other studies on this topic: attending a standardized statewide preschool program benefited disadvantaged children, but the effects soon washed out as they entered school.

There are many potential reasons to subsidize childcare, like the fact that it means the taxpayer shoulders some of the cost of raising children. But if weakly evidenced improvements to children’s future earning potential are cited as a reason, this raises questions about whether public money is being properly spent.

Throwing the baby out with the bathwater

When we raise the bar for what counts as ‘good enough’ parenting, people tend to have fewer children. South Korea, where it is normal for children of all ages to be very intensively and expensively tutored outside school, has the lowest fertility rate in the world at just 0.8 children per woman.

Hysteria over daycare causes needless anxiety to parents and potential parents. A couple who believe that daycare is harmful may delay parenthood until they can afford for one of them to stay at home, or feel guilty if they do have to use daycare. Others may worry that the wrong choice of preschool could lead to a lifetime of educational disadvantage.

Commentators on the left and right have their own reasons to make sweeping claims on daycare. But by framing the debate in this way, they are misrepresenting science and causing needless worry. This may even prevent some children from being born at all.

Enough studies have been conducted on daycare that if there were large, lasting impacts on children, either positive or negative, we would probably know by now. On a population level, any effects of daycare are small enough not to be obvious. Families should be encouraged to do whatever works best for them without worrying that it will damage their children.

Phoebe Arslanagic-Little is a writer and think tanker.

Ellen Pasternack is an editor at Works in Progress.

Watch the TED talk

I’ve also written a longer companion article for Works in Progress, which was published last week – you can read it here.

I think we’re at a turning point when it comes to medical innovation. Our tools are improving rapidly, but our ambitions to use them have fallen behind. Science funding has slowed down, aid budgets have been slashed, and immigration restrictions mean we’re driving away expertise. Even when things have come back online, the disruption and loss of expertise will make it hard to return to our previous trajectory. We could be doing so much more. Medical innovation might not seem urgent in the abstract, but most of us know someone whose life it could change, and eventually I think it affects us all. We can change that.

That’s part of the motivation for my writing on global health and medical innovation at Works in Progress and my work on clinical trial reform at the Abundance and Growth Fund, but the talk is also larger than that: it’s a call to arms for more people to work on medical innovation, and explains why you don’t have to be a scientist to do it.

I hope you enjoy it!

Reading list

The talk covers lots of topics I’ve previously written about or covered in podcast episodes. Here’s a list if you’d like to read more:

• The Golden Age of vaccine development The first vaccine was a lucky accident. Now we can design new vaccines in weeks, atom by atom. [Works in Progress]

• Death rates from cardiovascular disease have fallen dramatically Over a century of progress in surgery, drugs, prevention, and emergency response has driven down death rates from heart disease and stroke. [Our World in Data]

• Childhood leukemia: how a deadly cancer became treatable Before the 1970s, most children affected by leukemia would quickly die from it. Now, most children in rich countries are cured. [Our World in Data]

• Why we didn’t get a malaria vaccine sooner (written with Rachel Glennerster & Siddhartha Haria) Hundreds of thousands of people die from malaria each year, but it took 141 years to develop a vaccine for it. [Works in Progress]

• Lenacapavir: the miracle drug that could end AIDS (episode co-hosted with Jacob Trefethen) Saloni and Jacob talk about the development and prospects for this new drug, as well as the history of HIV, the initial discovery of retroviruses, and how HIV was transformed from a death sentence to a manageable condition. [Hard Drugs]

• Should everyone be taking statins? (episode co-hosted with Jacob Trefethen) Heart disease is the leading cause of death worldwide, but it’s also one of medicine’s biggest success stories. [Hard Drugs]

• Medical breakthroughs in 2025 An end-of-year round up of the biggest news in biotech and medicine that I wrote last year. [Scientific Discovery]

Martin Gould and Koji Flynn-Do explain why animals’ lives might, finally, be about to get better.

In September 2022, a new kind of pig farm opened in China: a twenty-six storey high-rise in Ezhou, near the Yangtze River. Months later, a second tower went up. Inside, pigs are kept by the tens of thousands on each floor, monitored by cameras and fed, watered, and moved with mechanical precision. More than a million pigs are born, raised, and slaughtered each year without ever setting foot outside.

These high-rise factory farms are only one example of a common pattern. As countries get wealthier, farming consolidates into fewer, larger, more brutal farms. Once average incomes reach around $1,000, chicken farming starts to industrialize. By the time a country reaches $10,000, the vast majority of chickens are raised in battery cages. In countries with average incomes above $30,000, almost all pigs are raised in warehouses.

Factory farming exists to meet rising demand for meat. Meat is tasty, nutritious, and much more expensive than rice or bread. As people get richer, they want more of it. When Park Chung Hee took power in 1961, South Korea’s meat supply was around four kilograms per person per year, less than the weight of two chickens. When his rule ended in 1979, that figure had quintupled. By 2000, it had increased tenfold. Today, the average South Korean eats more than 120 kilograms of meat and seafood combined per year.

Share

In poor countries, where inadequate nutrition is the norm, rising meat consumption is good for people’s physical development and health. Diet is only part of the story, but the pattern is unmistakable. In South Korea, average male height has increased from around 160 centimeters in 1961 (five feet three inches) to around 175 centimeters (five feet nine inches) today. Chinese men have seen a similar height gain: from around 165 centimeters before the country industrialized to around 175 centimeters today.

But industrially farmed animals suffer immensely for it. Chickens’ beaks are frequently sheared off and their legs are too weak to support their bloated bodies. Pigs have their tails docked and teeth clipped without anesthesia, and mother pigs live much of their lives in gestation crates too small to turn around in. These lives are not worth living. The question is whether such brutal treatment is inevitable.

For many of modernity’s worst problems, a combination of affluence, maturity, and political pressure has created self-correcting mechanisms over time. As countries got richer, things that initially worsened due to industrialization eventually improved. Will industrial meat production follow the same path?

The Kuznets curve

In his 1853 masterpiece Bleak House, Charles Dickens memorably described the air pollution of industrializing London: ‘flakes of soot … as big as full-grown snowflakes’. When Dickens was writing, London’s air pollution had been steadily worsening for decades as Britain industrialized, and it would continue to worsen for nearly half a century longer. But had he returned a century later, he would have found the dirtiness of London’s air to have halved, and by 2000, it would be less than a tenth as dirty.

Growing economies and populations have historically driven deforestation. But improvements in crop yields have halved agricultural land per person since the Green Revolution of the mid-twentieth century. The rate of global forest loss peaked in 1980, and forest loss typically reverses when average incomes enter the range between $5,000 and $15,000, as farming becomes more efficient and marginal farmland reverts to nature.

These trajectories are called Kuznets curves, after the economist Simon Kuznets, who suggested that economic inequality rose as countries first industrialized but then fell as they became even richer. His curves appear in many places. Wealthy areas clean up their local air, forests, and factories. Their inhabitants are less obese than those of industrializing countries, and have more leisure time and better working conditions.

But Kuznets curves don’t appear in all places, especially not when the industrial activity has no direct costs for the rich country. Emissions have fallen substantially in Germany and Britain, but much less in America and Australia, which remain some of the world’s biggest carbon emitters. The total amount of material people consume, and the amount of waste they generate, do not seem to decline but rather keep growing. The question is whether animal suffering is closer to child labor, and will decrease as we grow richer, or to waste generation, meaning animals will continue to suffer in ever-greater numbers.

Subscribe now

How much meat do we eat?

Start with consumption. In about ten European countries, including Germany, Austria, the Netherlands, and Denmark, meat consumption per capita appears to have peaked. Northern Europeans ate far more meat in the early 2000s than they do now.

Walk into a German supermarket today and the change is visible. The queue at the butcher counter has thinned; the same floor space now splits between marinated chicken, ready meals, and plant-based sausages. Pork, once the unquestioned centerpiece of German cuisine, has lost its grip: consumption fell over 10 percent just in the five years before 2025. The shift is even more noticeable in institutions. Forty years ago, a daily university menu would have centered on schnitzel and pork stew. Today, similar establishments compete to offer the best vegetarian and vegan options. In 2021, 34 cafeterias across Berlin’s universities moved to menus that were 96 percent plant-based.

But many rich countries aren’t like Germany or Denmark. Average incomes reaching $40,000 or $50,000 do not reliably herald a decline in meat eating. A more common story is a plateau. This is not bad news, as it implies that there is something of an upper limit on meat consumption. The plateauing countries, like Portugal, Spain, the United States, Britain, South Korea, and Australia, have all reached a ceiling of around 150 kilograms of meat per person per year.

Whether this ceiling holds may depend on shifting dietary fashions. Faddish new guidelines recommend eating two grams of protein per kilogram of body weight every day. If half of that protein were meat, the average American would need to double their meat consumption to meet the target. Drugs like Ozempic suppress appetite and reduce total caloric intake, but evidence suggests users shift toward protein-rich foods to preserve muscles, which could mean less food overall, but with perhaps a higher share of it meat and dairy.

More importantly, the kind of animal being eaten has changed. While Germans, Austrians, and Danes are consuming less meat, their diets are leading to the farming of more animals. In 1980, the average German diet required the slaughter of about ten farmed animals per year: roughly six chickens, one and a half pigs, and a third of a cow. By 2022, even though Germans were eating a fifth less meat, that number had doubled to twenty animals, largely driven by the shift to chicken and farmed fish: roughly 14 chickens, a bit less than one pig, one sixth of a cow, and six farmed fish.

From a welfare perspective, that makes a tremendous difference. Beef implies perhaps a day or two of suffering per kilogram, whereas chicken implies dozens of days of suffering per kilogram and farmed fish hundreds or thousands, depending on the species.

How we treat farm animals

Perhaps the continued high meat consumption in rich countries should be expected. The Kuznets curves for emissions of sulfur dioxide, particulate matter, and water pollution were not created by people consuming less. They were produced by people consuming differently. Cities increased the amount of heating in homes, but replaced coal with natural gas. People wash more laundry than ever, but the detergents no longer include phosphates. The way down the curve might not require people to eat less meat, but simply to produce it better.

For decades, the animal agriculture industry has focused on efficiency: cheaper feed conversion, faster growth, more animals per square foot. The result is that meat, eggs, and dairy are historically cheap. In 1946, the average American factory worker had to work more than half an hour to buy a pound of chicken. Today it takes four minutes. That single-minded focus on cost means there are now a lot of cheap, simple changes farmers can make to improve animal welfare.

Egg production is one example. For almost a century, farmers around the world have confined laying hens to battery cages offering less than a sheet of paper’s worth of floor space per hen. This comes at considerable cost to the welfare of hens, who cannot perform natural behaviors like spreading their wings, dustbathing, and nesting.

In wealthy countries, consumers and companies have shifted to producing and purchasing more cage-free eggs. Today, 45 percent of American, 62 percent of European, and 82 percent of British hens are kept in cage-free facilities. That amounts to hundreds of millions of hens spared from cages each year. Hens get two to three times as much floor space, which means each egg costs one or two cents more to produce. Richer consumers are willing to absorb those small costs.

In some countries and regions, cages for hens have been eradicated at the ballot box. Voters in rich places like Switzerland, Massachusetts, and California have elected to ban battery cages with resounding majorities. The Swedes didn’t even need legislation. By 2025, almost all hens in Sweden were cage-free thanks to retailers and shoppers rejecting caged eggs.

Other practices in husbandry are following a similar path. The European Union and United States now both require cattle and pigs to be stunned before slaughter, though exemptions exist for religious slaughter. Crates that confine pregnant sows and baby cows to spaces too small to turn around in have gradually been banned across the European Union, New Zealand, and several US states since the 2000s. Tail docking and castration without anesthesia, once standard for pigs, are restricted in the European Union and Britain.

New technologies can reduce suffering even further. In ovo sexing allows farmers to figure out the sex of chicks at the embryo stage, discarding eggs containing males. Adopting the technology means farmers avoid gassing or grinding up male chicks on their first day of life. The practice has already spared hundreds of millions of chicks from that fate in Europe, and has only just started spreading in the US.

Overall, these welfare improvements aren’t enough to offset the increased number of animals being farmed around the world. The sheer growth in the number of animals consumed, particularly chickens and fish, swamps the gains from better treatment. But in a few countries, the combination of declining meat eating and improved treatment is plausibly decreasing total farm animal suffering. New Zealand has banned battery cages, restricted sow crates, and mandated pre-slaughter stunning, and is also eating far less meat. The same may be true in Germany, Sweden, and a handful of other wealthy European countries. They offer a glimpse of what the other side of the curve might look like.

Subscribe now

Bending the curve

Income needs to reach a certain level before things can start to change. Whether you ask people in Sudan or Singapore, roughly the same share – between 70 and 90 percent – will tell you that they believe farm animals experience suffering and that their welfare matters. What changes with wealth is willingness to pay. In European surveys, 42 percent of the poorest quintile say they would pay more for higher-welfare products. Among the richest quintile, it’s 72 percent. No poor country has bent the curve: New Zealand has an average income of $45,000, Germany $55,000, and Denmark $65,000.

But income alone doesn’t guarantee progress. There are many countries that have surpassed these income levels and still have increasing meat consumption and less stringent farm animal welfare reforms than their peers. These include large economies like Japan, South Korea, and the United States.

Animal welfare improves fastest when the technology is already cheaply available. Stunning machines for chickens and pigs and cage-free housing systems for hens were cheap and effective before they started to be adopted at scale. Plant-based meat alternatives or lab-grown meat have yet to make any real dent in animal suffering: the entire alternative meat industry has yet to reach more than 2 percent market share for meat overall. This is easily explained by costs.

The only cultivated meat currently sold in supermarkets comes from a Singaporean company: a shredded chicken product that is 3 percent cultivated chicken cells and 97 percent plant-based, and retails at more than twenty dollars per pound. That is roughly ten times the price of conventional chicken and around five times the price of even premium products like pasture-raised chicken.

The failure of alternative proteins to make much of a difference in the past few years does not look so damning when we look at other Kuznets curves. For most of the twentieth century, leaded gasoline poisoned children’s blood across the developed world until lead levels plummeted within a decade of countries phasing it out in the 1970s. The air pollution that Dickens encountered steadily worsened for two centuries before its precipitous decline. Those curves began to bend when the problem became undeniable at the same time as a workable substitute existed. If indeed there is a Kuznets curve for animal suffering, it may take a tremendous amount of time and effort before we see the other side. What we see now is only a glimpse.

Koji Flynn-Do is chief of staff for US policy at LawAI.

Martin Gould is a Program Officer at Coefficient Giving.

Subscribe now

Medical innovation has transformed our lives, but hardly anyone realizes it. You can tell people that global life expectancy has doubled in a century and watch it fail to register – it just sounds like an abstract number, and numbers don’t convey how different life used to be. So let me describe it another way.

If you collapsed with a heart attack in 1950, hardly anyone around you would know how to help. CPR wouldn’t be invented for another decade. If you reached a hospital, a doctor would likely give you morphine, tell you to lie still and hope for the best: the prevailing view was that once the heart stopped pumping, nothing could be done.

That changed in the 1970s. Cardiologists began to understand that with each passing minute, more heart muscle would be starved of oxygen, and once dead, it wouldn’t be able to recover. But doctors could limit that damage by swiftly restoring oxygen supply with a clot-busting drug or a balloon catheter, opening blocked blood vessels and rescuing heart muscle.

In other words, the idea that a heart attack is something you could actively treat is only about fifty years old. Since then, the share of patients who have died within a month of having the most severe type of heart attack has fallen by two thirds.

Zoom out to cardiovascular diseases overall, and the trend is even more dramatic. People in rich countries today have roughly a quarter the chance of dying from cardiovascular diseases as they did in the 1950s at the same ages. Back then, there were no statins, no cholesterol testing, no bans on trans-fats, no anti-smoking campaigns, no bypass surgery, and no implanted pacemakers.

Diabetes, certain cancers, infectious diseases and other conditions have also become far more treatable than they used to be. A century ago, if you were diagnosed with type 1 diabetes, your remaining life expectancy would be a few months, and a ‘starvation diet’ would be one of your few options. Today, you’d simply need to wear a small device on your arm to track your blood sugar level and release insulin to stabilize it in real time. A century ago, it was unheard of for anyone to be cured of cancer, except, in rare cases, by a surgeon’s knife. Penicillin hadn’t been discovered, and a simple wound infection could result in sepsis and death. Smallpox still existed. It swept across the world and killed millions globally, year after year.

I think we underestimate how much medicine has progressed because we rarely experience life without it anymore. But it has added years, sometimes decades, to people’s lives. Maybe surprisingly, it’s also reduced inequality in life expectancy: we’ve seen greater gains at the bottom of the distribution, among those who would have died as children or young adults. At the same time, life expectancy has risen at every age.

The statistics go like this. In 1950, the shortest-lived 1 percent of babies born in France lived less than three months. But for babies born after that, that 1 percent started surviving longer and longer: up to six months for those born in 1960, three years in 1970, 18 years in 1980, and 25 years in 1990. Alternatively, you can think about the cohort you went to school with. If you were born in France in 1900, only two thirds of your cohort would still be alive with you when you reached the age of sixty. But if you were born in 1960, 90 percent of them would.1 So here’s another way to think about the rise in life expectancy. It means that far fewer parents lose their children, fewer children lose their siblings, and we grow old with more of our friends and family still alive.

A technological revolution

I used to have the impression that medical breakthroughs were uncommon; sometimes happening by pure chance, sometimes by sheer determination. I now see it as a continuous stream of medical innovation every year.

In the last few years, we’ve had new antiviral drugs against HIV that can prevent infections with nearly 100 percent efficacy, with just a single dose given every six months. There are new drugs that reduce cholesterol levels by 60 percent for people already on statins. There are new treatments that slow the progression of cancers, including certain lung cancers, brain cancer, pancreatic cancer and multiple myeloma, by more than half. And over the past five years, we’ve had the first vaccines against four more diseases: Covid-19 of course, but also the first malaria vaccine, the first chikungunya vaccine, and the first RSV vaccine.

For most of our history, finding effective new treatments really was a rare occurrence. After Edward Jenner discovered the first vaccine, it took nearly ninety years for scientists to work out how to develop the second. People relied on plants and natural remedies for centuries, with little idea of which ingredients worked or why. Some of these remedies were effective, but contamination was common, and without knowing their active ingredients, they couldn’t be produced reliably at scale.

After chemistry matured into a scientific discipline in the nineteenth century, it became possible to isolate and purify compounds, synthesize new ones, and screen hundreds or thousands at once to find those that had medical effects. Chance discoveries could now be made systematically, and chemists discovered medicinal compounds in soil (yielding antibiotics like streptomycin, vancomycin, and tetracycline), fungi (statins and immunosuppressants like cyclosporin), and coal tar and dyes (sulfa antibiotics and early anesthetics like benzocaine). It was a valuable strategy when little was understood about the biological causes of diseases or the mechanisms of drugs.

By the late twentieth century, new tools, theory, and knowledge made it possible to develop treatments based on better biological understanding in an approach that became known as ‘rational drug design’. Scientists learned to decipher the structure of the proteins that drove disease and design molecules to fit into them and block them. They began to grow and study living cells in the lab, engineer bacteria and yeast to bulk-produce proteins (including insulin, clotting factors, and antibodies), and automate the screening of hundreds of thousands of compounds in days. It all became faster and possible at a far greater scale. Back when the Human Genome Project was completed in 2003, it cost $50 million and took six months to sequence just one person’s genome. Now it costs a few hundred dollars and takes under four hours. The tools have also gotten sharper. Over the past two hundred years, the resolution of the best microscopes has increased over ten-thousandfold. Until the 1930s, no one had ever seen a virus. Now we can see them down to their atoms.

Advances in AI are taking us further. Tools like AlphaFold can help predict the shape of proteins in minutes rather than years. Others are being used to design entirely new proteins that don’t exist in nature, including enzymes that catalyze reactions no natural enzyme can and proteins that target cancer cells and destroy disease-causing proteins within them. Some tools can identify hidden microbial genes that encode antibiotics but aren’t expressed under standard laboratory conditions. Others have uncovered ancient versions of today’s CRISPR enzymes, much smaller than the ones we use now but still able to protect bacteria from viruses. They have turned up entirely new classes of gene-editing tools that can precisely cut and paste long stretches of DNA, allowing them to fix multiple genes at once.

Much of the early research behind these breakthroughs takes place in academic labs and institutes funded by governments and foundations, before they are developed into drugs, manufactured, tested in large clinical trials, and brought to market by pharmaceutical companies. The first antiviral drug against HIV, for example, came from cancer researchers at the National Cancer Institute, who systematically screened hundreds of drugs to test whether any of them inhibited the virus before eventually identifying AZT. Burroughs Wellcome (now part of GSK) then ran the clinical trials to get it licensed. Similarly, the GLP-1 hormone was identified by academic researchers in the 1980s, but it was scientists at Novo Nordisk who developed drugs that mimicked it and chemically modified them to last long enough in the body to be used medically for diabetes and weight loss.

Competitive pressure generally causes firms to underinvest in open, early-stage research: if they publish it, other firms can use their findings without contributing; if they don’t, others can’t test, challenge or learn from their work. So private firms tend to focus on later-stage research, predominantly for diseases with a large commercial market, as they are better equipped to do the capital-intensive work of running large clinical trials, navigating regulators, and scaling manufacturing than academic institutions and foundations. Together, this process of exploration, discovery, development, and scaling has transformed once-fatal diseases into manageable, and sometimes even curable, conditions.

Medical innovation is one of the most valuable things that happens in a modern economy. Economists estimate that gains in life expectancy in the United States from 1970 to 2000 were worth about $95 trillion to Americans, with roughly half of that coming from reductions in heart disease mortality.

Share

Bottlenecks and broken incentives

There are almost certainly effective treatments in the pipeline today that won’t reach patients for years, sometimes decades, and it’s not because of the science.

There are few better examples than the malaria vaccine. Malaria is a very complicated disease: it’s caused by a parasite that changes shape multiple times during its life cycle, making it very hard to know what to target with a vaccine. So the first malaria vaccine, introduced just a few years ago, was an amazing scientific breakthrough. But it was actually developed in the 1990s. The researchers who developed it struggled to find funding to test it at every stage of the process. There was little commercial incentive. It’s not profitable to develop vaccines for diseases that affect people in poorer countries, without being able to recoup the R&D investment – even if millions of children might benefit and there’s a huge economic return. It took foreign aid and philanthropy to fund it, and it took literally decades to reach children who needed it, even as half a million of them were dying from malaria every year.

Those children aren’t coming back. But we can prevent this from happening again. Economists have come up with an idea to change the incentives with an advance market commitment, where donors promise ahead of time to buy a vaccine at a certain price per dose. The payout occurs only if it’s developed, and proven safe and effective. The commitment gives companies the confidence to invest, and can bring vaccines into existence that would otherwise never get made. Most importantly, it makes sure they’re manufactured at scale and sold at an affordable price, so they reach those who need them.

That idea was used over a decade ago to develop new vaccines for pneumococcal disease, a deadly bacterial infection of the lungs and brain. Pneumococcal vaccines already existed, but they didn’t include the strains common in Africa and South Asia. In 2009, several countries and philanthropists came together to fund an advance market commitment for new vaccines and it succeeded: several companies developed them and they reached children much faster than usual. It’s estimated that those vaccines have saved the lives of over 700,000 young children since then.

For all that, malaria is one of the better-funded global health diseases. Roughly $4 billion is spent on R&D across all tropical diseases combined each year, or around six cents for every thousand dollars of income in wealthy countries. Two thirds of it goes toward tuberculosis, malaria, and HIV. For the rest, the research pipeline is incredibly narrow, if it exists at all. One example is trachoma, a painful bacterial infection of the eyes that’s spread by flies. Repeated infections scar the eyelids, which gradually turn inward until the eyelashes scratch the eyes. Eventually, the scarring clouds the cornea, causing the person to go blind. Although we’ve made a lot of progress against new cases of the disease with antibiotics, around 400,000 people worldwide are blind because of the disease, and the pipeline of new diagnostics, treatments and vaccines in development for it is nearly empty, with R&D spending in 2023 falling to zero.

Many other tropical diseases, like leptospirosis, scabies, Buruli ulcer, mycetoma, and yaws, receive almost no R&D funding, and have research pipelines so thin they can support only a few dozen researchers worldwide. For some, like mycetoma, even the basic biology is mysterious, with little understanding of which molecular pathways drive the disease or how to target it with drugs.

The problem extends far beyond diseases of global poverty. Rare diseases, conditions affecting fewer than 1 in 2,000 people, are another example. Thousands of rare diseases have been described, and they collectively affect up to 6 percent of the population. But each disease is rare enough that the financial market for new drugs is limited and patients are often abandoned entirely; 95 percent of these diseases don’t have any approved treatment at all. Running trials for these conditions takes thinking differently: using smaller but more efficient trials, more coordination between researchers, and different approval pathways. For instance, many new gene therapies edit or silence specific harmful genes. Once researchers have found a safe way to get these therapies inside the cells where they’re needed, regulatory systems could treat the delivery method as a single platform, allowing the particular genetic sequence to be switched out to target different mutations of the same disease, or even different genetic diseases, without needing new approvals each time.

Or consider childhood leukemia. It used to be very difficult to test treatments for the disease because it is rare, and individual hospitals struggled to find enough patients to run clinical trials. So, from the 1960s onward, researchers built networks to recruit patients from across the US, and later Canada and Europe into larger clinical trials. That collaboration made it possible to learn what worked faster, and it’s why leukemia is no longer the disease it used to be. When I used to hear the phrase childhood leukemia, I’d picture a child who suddenly fell ill and whose parents were told they only had a few years left to live. That has changed. Before the 1970s, only 15 percent of children with leukemia would be alive five years after diagnosis. Now that figure is 85 percent. Most children in richer countries today survive and are effectively cured of the cancer.

These problems fall especially hard on tropical and rare diseases, but poor economic incentives mean we’re missing out on medical innovation across the board. Some of the biggest breakthroughs in medicine have been drugs developed for one condition that turned out to be effective for others, like GLP-1 drugs, which were initially approved for diabetes before being used for weight loss. Or SGLT2 inhibitors, which were also originally developed for diabetes, and have since turned out to be effective for treating heart failure and chronic kidney disease as well. This kind of ‘drug repurposing’, where companies test their own drugs for new uses, can be very profitable, but the incentive is time-limited: once a drug goes off patent and cheaper generics enter the market, the reward for running large expensive trials disappears and firms stop seeking approval for new uses. We don’t find out whether the drugs would have worked, and patients who might have benefited can’t access them.

Often, we may have many plausible candidates but no cheap way to test them. One way to fix this is through platform trials, which test multiple treatments for a single disease using a shared control group, which lowers the cost of testing each one and makes it possible to compare a range of treatments directly with one another. The RECOVERY trial in the United Kingdom, for example, tested over a dozen drugs as potential Covid treatments in a single trial over two years, at a fraction of the typical cost. Within a few months of the beginning of the pandemic, the trial identified that dexamethasone, a generic drug, was effective against Covid, cutting deaths by around a third among the sickest patients on ventilators. Its use is estimated to have saved hundreds of thousands of lives since then. The trial also ran much faster than usual, because participants were recruited through the UK’s National Health Service with simple, streamlined ethical approvals and consent forms.

The deeper problem is that technology isn’t always the barrier: sometimes it’s about the funding, the incentives, and the institutions. While genome sequencing costs have plummeted and the resolution of microscopes has surged, productivity in drug development has actually slowed down: the cost of getting a drug to market has been doubling in real terms every nine years for decades. This phenomenon was first described by Jack Scannell, who coined it ‘Eroom’s law’, the reverse of Moore’s law, which says that transistor chips roughly double in density every two years, allowing smaller and cheaper computers. The slowdown may be part of a broader trend: across many fields, including semiconductors and agriculture, the number of researchers has risen while the output per researcher has fallen and productivity has slowed down.

One explanation is that the lowest-hanging fruit is gone: many medicinal compounds in nature have already been screened, for example, and newer ones take more resources to discover. But given how much our tools of discovery have improved, I’m not convinced. More persuasive, I think, is the ‘better than The Beatles’ problem: new drugs not only have to be safe and effective, they have to be superior to the current standard of care, meaning they must clear a bar that rises with each generation of successful treatments. This isn’t just because older drugs already have some efficacy, but also because many have gone off patent and become generics, meaning they can outcompete new drugs on price as well. And as existing treatments improve and diseases become milder, it becomes statistically more challenging to confirm the benefits of new drugs, requiring larger or longer clinical trials.

It’s also become much slower and more complicated to run clinical trials. Before a drug can be approved, it must pass through successive stages of trials, with more participants and more data collected at each stage, before the data is submitted to regulators and approved for medical use. That overall timeline has grown from an average of six years in the 1970s to eight to nine in the 2010s.

Currently, each trial is built from scratch, with its own infrastructure, contracts and administrative overhead. Before a single patient is enrolled, each hospital or research center running the trial must review the protocol, negotiate contracts, obtain ethics approval and train staff; this process takes several months for each trial. Recruiting enough participants is then another challenge: trials seek out patients who meet narrow eligibility criteria, are willing to be randomized to treatment or placebo (meaning they may not receive the treatment at all), and will return to a clinic for follow-up visits sometimes dozens of times over several years. Around half of trials fail to recruit as many participants as planned; only one in five finish on time, with median delays of over a year. On average, it costs $54 million in the US, or around $37,000 per patient, to run a single late-stage trial for a single infectious disease drug.

The bureaucracy that surrounds trials today is largely a legacy of global regulatory guidelines introduced in the mid-1990s, which the trials industry interpreted defensively to minimize the risk of regulatory rejection. Even when regulators have since rolled back specific requirements, companies have been slow to change. Around a third of trial costs, for example, come from the practice of ‘source data verification’, where a consultant manually cross-checks every data point collected at trial sites against paper records, despite the FDA recommending against it because it catches few errors while adding huge costs. Because less than 10 percent of drugs that enter clinical trials are approved and the costs of development are large, the industry has remained financially risk averse, doing far more administrative work than is required, and far less efficiently than the process could allow.

That doesn’t mean we should sidestep the process of rigorous testing. Clinical trials are the best way to test whether drugs are actually effective, how effective they are, and what side effects they carry. Without them, we can’t reliably identify which drugs actually work, and we can easily be misled by random fluctuations, natural improvements over time, and selection biases that make drugs appear effective even if they have no benefit or actively harm patients. But the whole process could be much more efficient. It’s possible to speed up medical innovation without cutting corners or compromising on rigor, or better, through win-win solutions that improve both.

Subscribe now

A cure for every disease

Far too many diseases are still untreatable. It’s painful to imagine gradually forgetting your children’s names, forgetting how to hold a conversation, how to recognize your own home, and eventually even how to swallow food, while your family watches someone they love disappear. But that’s the reality for over thirty million people with Alzheimer’s globally, and we have almost nothing to offer them. Part of the reason may be because the brain is so complex, or because it’s lined by the blood-brain barrier, a tightly sealed layer of cells which keeps out most pathogens and toxins, as well as most drugs. That makes it challenging to design a drug that can cross the barrier, reach the right cells, and do what it’s meant to do without any unexpected side effects.

Cancer is not a single condition but hundreds of distinct diseases, driven by different genetic mutations, that can evolve rapidly and become resistant to each drug. Treating them often requires combination treatments, which attack cancers from multiple angles to reduce the chances of resistance developing, but many cancer drugs carry side effects that are highly unpleasant or even debilitating. Often, the only available options are chemotherapy or radiation therapy, which attack healthy tissue alongside tumors, causing lasting damage to the body.

I’m hopeful that progress is possible. Many conditions that once seemed untreatable have turned out not to be. Hepatitis C is now curable. Some diseases are now entirely preventable with vaccines, including cervical cancer and many liver cancers. Multiple liver diseases can be halted by new drugs that silence key proteins that drive their progression. CAR-T cell therapies, which reengineer a patient’s own immune cells to kill their cancer cells, mean that several blood cancers can now be put into lasting remission, and sometimes cured. New treatments have given cystic fibrosis patients lives that look much like anyone else’s, when they would have otherwise died in their twenties or thirties.

The most dramatic example is pancreatic cancer, one of the deadliest cancers, which has had a five-year survival rate of just 13 percent. It’s long been thought to be untreatable, because it is driven by mutations in the KRAS protein, which is notoriously hard for drugs to target because the surface of the protein is smooth, without an obvious pocket for drugs to bind to and block. In the last decade, however, breakthroughs in understanding the protein’s structure and interactions have helped develop new drugs that recruit a second protein to grab onto KRAS and block it. A new large phase three trial found that one such drug, daraxonrasib, roughly doubled survival compared to standard chemotherapy. Its side effects are rough, but knowing how to target the protein at all means scientists can build upon it. That work will be slow and difficult, but decades from now, we’ll look back and see the trajectory has changed, as it did for leukemia.

The list of bottlenecks is long, and we need to move faster if we want to solve them before it’s too late for too many people. It takes years to find and recruit patients for clinical trials and clinical trial infrastructure is highly fragmented. Commercial incentives mean that firms have little desire to develop drugs for many diseases whose patients are too few or too poor for it to be profitable, and there’s little incentive to repurpose drugs for new uses once patents run out. People have already come up with some ideas to solve them, including platform trials, advance market commitments, prizes to incentivize drugs for neglected diseases, risk-based monitoring of trials to focus on the highest-risk elements rather than on cross-checking every data point manually, large simple trials that operate through existing electronic health records, and continued randomization after a drug is approved to learn which dosing strategies, treatment durations, and drug combinations work best. But we also need new ideas, and people to test them, scale them up, and see them through.

We can make progress even in the hardest of cases. Ebola vaccines are incredibly challenging to develop through the regular route for many of the same reasons. There was little commercial incentive: Ebola largely affects the poorest, and its outbreaks are unpredictable, which makes it hard to set up trials in time. But what’s amazing is that we have a vaccine for the Ebola Zaire virus. Just over a decade ago, Gavi created an advance market commitment to fund it, and scientists came up with a different way to run clinical trials: ring vaccination. They waited for individual cases of Ebola to appear, and then quickly vaccinated the contacts of affected people, testing how well the vaccine prevented new infections. The World Health Organization coordinated the trials, the US government helped fund the vaccine’s development through BARDA and the Department of Defense, and once the vaccine was licensed in 2019, Gavi, WHO, UNICEF, and the Red Cross set up a global stockpile so doses would be ready for another outbreak. That stream of innovation, I’ve realized, is the result of countless people who thought differently, whether they were scientists, economists, managers or operators. Some of them changed their lives to make it happen. What they recognized was something quite simple: that diseases are not a fact of life, but problems that can be solved.

I’ve been writing about global health and medical innovation for years, and when I tell friends and family how much progress there’s been, the reaction is almost always the same: they had no idea most of it was happening. But progress isn’t inevitable, and breakthroughs don’t just come about when we have the tools to make them; they depend on how innovation happens in the real world. Right now, those processes are bottlenecked by funding, institutions and incentives. But we can change them. I think it’s more important than ever that we do so, because of cuts to spending on science, global health and foreign aid; we need to find ways to make our resources go further.

The central drama of the modern world is innovation against suffering, and we have made incredible progress so far. But we are doing far worse than we could. Millions still suffer from untreatable diseases, because of bottlenecks that we could fix. Fixing them is one of the most important things we can do. You can help make it happen.

Saloni Dattani is an editor at Works in Progress, writes the newsletter Scientific Discovery, and is an advisor to Coefficient Giving on clinical trial reform.

Share

In June 1973, chestnut colt Secretariat ran the Belmont Stakes so fast that no horse has matched him since. In less than two and a half minutes, Secretariat flew along the track, finally pulling away to win by 31 lengths, nearly three quarters of a football field. The other horses were so far behind they weren’t even in the television frame. Fifty years later, billions of dollars have been poured into breeding and training, yet Secretariat’s record still stands.

This is the paradox of the thoroughbred: breeders have spent centuries trying to create a faster horse, but in doing so, they may have bred away the very genetic diversity that would allow the horse to keep improving, or even to remain robust.

The paradox is not confined to the racetrack. The horse began as a terrier-sized, multi-toed forest dweller and, over 55 million years of evolution and a few thousand years of human intervention, became everything from the compact Icelandic pony to the streamlined racehorse. For most of that history, natural selection shaped horses slowly. Only recently has human ambition taken over, breeding animals for speed, endurance, and docility. The result is extraordinary diversity in form and performance, but also a dramatic narrowing of genetic diversity.

The first horses

The story begins 55 million years ago, deep in the warm, humid forests that covered what is now North America. You’d be hard pressed to recognize the earliest equid. Known as Hyracotherium, it stood only 14 inches tall, closer to a terrier than a modern horse. With four toes on the front feet and three on the back, it was ideally suited to moving gingerly over soft, marshy ground and nibbling fruits and leaves.

When global temperatures rose, between 18 and 15 million years ago, the equid family diversified into more than twenty genera (the subdivision above species living in woodlands and savannas). Most of these lineages have long since died out: today, only the genus Equus survives, which includes horses, zebras, asses, and donkeys.

As grasslands spread, over millions of years, equids developed into the horses we see today. Few evolutionary stories are as well documented. In the nineteenth century, when paleontologist OC Marsh unearthed a rich collection of fossil horses in the American West, their significance was immediately recognized. Here, laid out almost step by step, was evolution in action: horses transitioning from small, many-toed forest-dwellers into large, single-toed animals that grazed on grass rather than eating fruit and leaves.

That single toe, of which the hoof is the toenail, is the evolutionary innovation key to horses’ success. Life on the plains favored animals able to run efficiently over long distances. Rigid, lightweight hooves help with this: they minimize sideways wobble while storing and releasing energy like a spring, much like the shoes a human sprinter might wear, or even the prosthetic running blades sometimes used by amputees.

Over millions of years, the number of toes fell gradually from several to just one. Between 43 and 33 million years ago, Mesohippus still sported three toes of roughly equal size, with each touching the ground. By the time of Hipparion, about 23 million years ago, the middle toe carried most of the animal’s weight: the outer two toes had shrunk into vestiges, and the middle toe had become dominant. Finally, Pliohippus took a pivotal step toward the modern form, with a single weight-bearing toe ending in a solid hoof. This evolutionary streamlining produced the feet of today’s horses: a single, sturdy keratin hoof perfectly suited for galloping over open ground.

The route to the modern horse involved several detours. Hyracotherium, the progenitor of the horse family, appears in the fossil record in North America from around 55 million years ago, disappearing again 8 million years later. Around 12 million years ago, Hipparion, which, though three-toed, otherwise resembled modern horses, colonized Eurasia. Hippidion, which had short limbs and distinctively shaped facial bones, roamed the plains and mountains of South America from around 3 million years ago. Then, around 2 million years ago, the most recent common ancestor of present-day asses and zebras crossed the Bering land bridge formerly joining Alaska and northeastern Siberia.

Within the next half a million years, their descendants rapidly expanded across Eurasia and entered Africa at least two separate times. The descendants of the first migration diversified into various zebras, while the second led to modern donkeys and African wild asses.

Although the Americas were home to the earliest proto-horses, horses (including Hippidion and others) later became extinct in the Western Hemisphere around 10,000 years ago, alongside other megafauna like giant sloths, human-sized beavers, and armadillos as big as cars. All horses in the Americas today, including the free-roaming mustangs of the American West, come from European horses introduced after the Spanish conquest – descendants of the branches of the horse family that crossed into Eurasia and avoided extinction.

Share

The first horse tamers

Exactly when, where, and how horses were domesticated remained a mystery until recently, because fossils of wild and early domestic horses look very similar. For decades, archaeologists pointed to the Botai people of northern Kazakhstan, who lived around 5,500 years ago, as the original domesticators. Excavations revealed corrals, possible evidence of harnesses, and even pottery with residues of horse milk, a clear sign that the Botai people were not merely hunting and eating wild horses but had integrated them into many aspects of their lives.

While the Botai horses seemed like the obvious ancestors of modern horses, DNA told a different story: when scientists sequenced the genomes of twenty horses from the Botai site, they were not genetically similar to modern domestic breeds. Instead, Botai horses grouped closely with the Przewalski’s horse (pronounced shuh-VAHL-ski), a species discovered roaming the Mongolian steppe in the late 1870s and long considered the only truly wild horse.

This means that, contrary to the long-held belief that Przewalski’s horses were the last surviving truly wild horses, they are instead the feral relatives of the earliest known domestic horses found at Botai. While the Botai likely did domesticate horses first, their culture died out and their horses returned to the wild.

From steppe to stable

The horses we know and love came from a different source. They emerged more than a thousand years later, about 4,200 years ago, in the Pontic-Caspian steppes of what is now southern Russia, the same region that gave rise to famous horse-riding warriors like the Cossacks, the Golden Horde, and the Huns.

Scientists have worked this out through genetic analysis of ancient horse remains, combined with carbon dating to establish their precise age. A foal inherits half of its DNA from each of its parents. This is passed on with almost incredible accuracy, with around 2.7 billion base pairs (the data units of DNA) being copied correctly, but even so a few dozen errors creep in each time. A scientist can take the DNA of an ancient ancestor from a fossil, compare it with the DNA of a modern descendant, and then estimate how many generations have passed by counting the number of mutations that have accumulated.

In 2021, scientists did just this, sequencing genomes from 273 sets of bones ranging from 50,000 to 200 years old. By looking at the mutation rate and carbon dating the bones to confirm their exact age, they could calculate how quickly generations passed. About 4,200 years ago, the generational clock began to tick twice as fast, halving relative to wild horses, suggesting deliberate breeding.

Although bones can’t tell us how ancient horses behaved, their genomes give us clues. The researchers found that certain genetic variants became unusually common in these steppe horses. Such a pattern signals strong selective pressure: something in the environment consistently favored animals carrying particular versions of genes.

One region under heavy selection lies near a gene called ZFPM1, thought to play a role in the development of brain cells involved in mood, fear, and aggression. This suggests that early breeders might have been either deliberately or indirectly choosing animals that were more docile, allowing training, handling, and eventually riding. A second region under strong selection sits just upstream of GSDMC, a gene linked in humans to spinal problems such as chronic back pain and narrowing of the spinal canal. The signal of selection at this locus in horses suggests that breeders may have favored genetic variants associated with stronger, more resilient backs. As horseback riding spread, horses that could bear weight without developing spinal pathologies would have been more desirable.

These steppe horses, known to geneticists as DOM2 (that is, domesticated lineage two), spread like wildfire. By 2200 to 2000 BC, the DOM2 genetic profile spread beyond its region of origin to Anatolia, the lower Danube region, and Bohemia.

Archaeological evidence suggests that as DOM2 expanded, the populations of other wild horses gradually dwindled. By around 1500–1000 BC, almost all had been either absorbed or replaced. The tarpan horse, which roamed Eastern Europe, became extinct in 1909. By 1969, Przewalski’s horse was declared extinct in the wild. All living Przewalski’s horses stem from just 15 individuals captured around the year 1900. Only in 1992 did the descendants, numbering about 2,000, begin to be reintroduced on the Eurasian steppes.

The many so-called wild horse populations found around the world, including mustangs, Sable Island ponies, and Australian brumbies, all descend from modern domestic horses that became feral again within the past few centuries.

Horses for courses

Over time, humans developed distinct horse breeds with a wide range of phenotypes, from the tiny Argentinian Falabella, barely reaching a meter tall at the shoulder, to the towering French Percheron, capable of hauling tons; from horses with the standard gaits (walk, trot, canter, and gallop) to horses able to perform alternative gaits, like ambling, with no bounce, making them more comfortable to ride. The Icelandic horse’s tölt is so smooth that a rider can carry a full glass of beer without spilling a drop.

This diversity is the product of millennia of human intervention, selection, and preference, which left distinct traces in the horse’s genome. Compared with many other species, horses have a lot of diversity in the mitochondrial genome, inherited from the mother, but extremely limited variation within the Y chromosome, passed down from father to son. This contrast suggests a pattern in domestication: many local mares (female horses) were bred with a fairly narrow pool of stallions (males), concentrating paternal lineages while preserving variety in the maternal line.

Ancient DNA has given us a window beyond fossils, allowing us to track how phenotypes changed in ways that don’t show up in the fossil record. After humans, horses are one of the species ancient genomics has studied the most. In fact, the very first successful recovery and analysis of ancient DNA was from 150-year-old tissue from the extinct quagga, a close relative of the zebra, in 1984 – a year before the same was achieved with ancient human DNA. One of the oldest genomes ever successfully recovered and decoded comes from a horse bone preserved in the Yukon permafrost for over half a million years.

Coat color offers another window into early horse breeding. In living horses, the genes behind colors and patterns, like leopard spotting, tobiano patches (like the coloring of a cow), and cream dilutions (that lighten the color of a horse’s coat), are well understood. Genetic variants for dun (gray-gold, or tan), black, and leopard spotting appear in wild horses from the Upper Paleolithic, long before domestication began.

In the early Bronze Age, leopard-spotted horses were abundant at Kirklareli-Kanlıgeçit in present-day Turkey. But leopard spotting comes at a cost: horses with two copies of the gene coding for it have night blindness (the inability to see in low light). Its prevalence in certain ancient populations suggests breeders made deliberate choices, where aesthetic or symbolic value outweighed the trait’s practical drawbacks, to favor certain traits unlikely to persist in the wild. Tastes shifted with time: leopard-spotted horses lost their appeal after the early Bronze Age but gained favor in some regions during the Iron Age. And while spotted coats were popular in antiquity, solid chestnut horses prevailed in medieval Western Europe.

In the Middle Ages, horses were inseparable from power and status. Chivalry itself shares an etymological root with the Old French chevalier, literally ‘horseman’. Breeding and maintaining horses became a major industry of nobility and royalty. But they didn’t think in terms of fixed breeds the way we do today. Medieval writers grouped horses by function: the destrier trained for combat, the courser valued for speed, and the palfrey prized for a comfortable ride. Archaeological evidence backs this up. A large study of horse remains from thirteenth- and fourteenth-century London shows a range of sizes and builds, not the uniformity that we would expect from tightly restricted breeding.

Contrary to the modern idea of the medieval warhorse as a massive, towering beast, measurements from excavated horse bones across England show that most stood around 13 to 14.2 hands high, roughly the size of a sturdy modern pony. Even horses associated with elite or military contexts rarely approached the heights of today’s heavy draught breeds. What medieval riders valued instead were animals that were compact (meaning cheap to feed), strong, and agile enough to handle long distances, uneven terrain, and the demands of warfare.

Subscribe now

The need for speed

By the seventeenth century, horses had been serving human purposes for thousands of years, plowing fields, carrying soldiers, and pulling carts. But in early-modern England, one goal came to dominate: speed. In the 1660s, King Charles II, a fervent horse racing fan, set up a horse breeding and racing center at Newmarket, near London. While horse racing had been popular in previous centuries, Charles II and other racing enthusiasts were the first to methodically breed horses at scale to improve their race performance.

Breeders discovered that horses from Arabia, Central Asia, and North Africa were often faster: they were lighter, had a greater drive to run, and were better able to dissipate heat, allowing them to sustain high speeds without overheating. From three exceptional horses imported to England, Byerley Turk (imported in the 1680s), Darley Arabian (1704), and Godolphin Arabian (1729), breeders created the ‘thoroughbred’, a new type of horse designed for speed. Today, 95 percent of all living thoroughbreds are thought to descend from just one of these stallions, Darley Arabian, through his phenomenally successful great-great-grandson, Eclipse.

Horse breeding used to be guesswork: breeders paired fast stallions with fast mares and hoped for the best. But in 1791, the General Stud Book started recording every thoroughbred’s ancestry, turning pedigree into data. Breeders could now track bloodlines, deliberately plan matings, and see which combinations actually worked. Thoroughbreds today are defined as horses whose ancestry can be traced entirely to horses listed in the General Stud Book.

Harder, better, faster, stronger

Racing and breeding evolved side by side. Races in the seventeenth and eighteenth centuries involved multiple heats over distances of two to four miles, favoring horses with stamina. Horses didn’t race until they were five or six years old. But by the late eighteenth century, new races like the Derby and the St Leger reset the terms of competition. Horses now raced at three years old, over shorter distances of one to two miles.

This new format meant an increased premium on speed and precocity, and it has persisted, particularly in the United States and Australia. In Britain and Ireland, the tradition of long-distance races held on in parallel, leading to distinct types: horses that specialize in explosive speed at a young age, classic middle-distance horses, and horses bred for the stamina needed to excel in longer races.

After the creation of the thoroughbred and the Stud Book, Anglo-American breeders hit what appears to be an upper limit for speed surprisingly quickly. From the middle of the nineteenth century, when timing and record keeping became good enough to make reliable comparisons, race times improved steadily for about half a century. But although there was consistent improvement, it was small: times only fell by 1 to 2 percent, or 2 to 4 seconds over a 1.5-mile race. Race times for prominent races have not significantly fallen since around 1910. Secretariat’s 1973 Belmont time eclipsed the previous record by a stunning 2.6 seconds. However, the best time since then (Easy Goer in 1989 at 2 minutes 26 seconds) was a full 2 seconds slower than Secretariat’s.

Outside the elite, there has been continued improvement: one study found that between 1997 and 2012, accounting for differences such as ground softness and the number of runners, the average British thoroughbred increased its speed by 0.011 yards per second per year. So while we have likely reached the ceiling for how fast an exceptional horse can run, the median horse is beginning to close in on that limit, too.

The genes for speed

Until 2007, the Stud Book was the cutting edge of horse breeding technology. That changed when scientists sequenced a horse genome for the first time, that of a thoroughbred mare named Twilight. This allowed researchers to study the genetic basis of variation between individual horses far more systematically.

Another step forward in understanding thoroughbred genetics came with a paper published in 2010 that investigated the gene in horses that codes for myostatin, a protein that regulates muscle development. Mice, cattle, dogs, and even humans with mutations in this gene grow outlandishly large muscles because the gene normally acts as a brake on muscle development; with that brake damaged, muscles continue to grow unchecked.

The gene coding for myostatin in horses has around 1,100 base pairs. Looking at the exact sequence of this gene, called MSTN, in 148 thoroughbreds revealed that horses could have three different versions of the gene, differing by just one of those base pairs (either a letter ‘C’ or a ‘T’), and that each version was associated with success in different race formats. Horses with two copies of the ‘C’ version tend to be the best sprinters, those with two ‘T’s tend to be high-stamina long-distance runners, and those with one of each tend to fall between the two running profiles.

Later research found that variations in MSTN correspond with different muscle physiology. Horses with the ‘C’ version have a higher proportion of fast-twitch muscle fibers, which enable the explosive bursts of speed required for short-distance sprint racing, while those with the ‘T’ version have a higher proportion of slow-twitch fibers, which allow sustained effort.

Analyzing the DNA of modern horses and museum specimens then showed that the foundation stallions in the Stud Book all had two copies of the ‘T’ variant, and that the ‘C’ mutation probably entered through local British mares. This new variant entered thoroughbred genomes during the late eighteenth and nineteenth centuries, as English races like the Derby and St Leger got shorter. But the genetic trend is less pronounced in Britain than the United States, where races are rarely longer than 2,000 meters, and especially than in Australia, which favors 1,000 to 1,400-meter lengths. Commercial tests for this gene are now widely used by breeders and trainers.

The price of success

Horses’ genetic diversity remained large for thousands of years, before collapsing after the introduction of modern breeding. In nature, diversity is maintained by competing selection pressures that balance one trait against another. A wild horse does not just need to be fast. Its bones need to last. It needs to be resistant to disease. Even a domesticated working horse would, before intensive breeding began, face natural constraints on its traits.

In modern thoroughbred breeding, celebrity stallions with the best race records are in high demand. Their owners charge hundreds of thousands of dollars in stud fees, and they can sire perhaps a hundred foals per year. This means that the genes of particular males can quickly sweep to dominance in a population in a way that would be very unusual in nature.

Along with this loss of diversity, modern horses have accumulated harmful mutations as a result of breeding within a small population. In horses as in humans, repeated inbreeding concentrates harmful traits as parents who are related to each other are more likely to share the same mutations, resulting in offspring with two copies of the mutated gene, rather than one mutated copy and one normal copy, which could mask the mutation’s effects.

A genetic analysis of all Australian thoroughbreds, more than 135,000 horses, showed that inbreeding correlates with slower, shorter, and less lucrative careers. Amazingly, ten heavily crossed eighteenth-century ancestors account for over 80 percent of inbreeding in Australian thoroughbreds. Breeders are not blind to these risks. The American Quarter Horse Association, for example, requires breeding stallions to be tested for several genetic diseases.

As genetics has played such a large role in breeding horses, it is small wonder that horse breeders are moving with the frontiers of science. The world’s first cloned horse, called Prometea, was born in 2003. Horse cloning is now big business, despite an American Jockey Club ban, as other equine sports, including show jumping and polo, allow clones.

In 2024, the Argentinian company Kheiron announced the production of the first CRISPR-edited horses: Polo Pureza, an award-winning mare, was the foundation for five gene-edited clones with increased explosive speed. According to reports, the company modified the MSTN gene, so that the animals would develop more muscle fibers and potentially run faster as a result. Even so, the prospects for exceeding current records through gene editing are slim. Today’s racehorses are already tightly optimized for speed, balancing strength against the cost of carrying additional muscle mass. Adding more muscle is relatively low-hanging fruit, and if this were the key to unlocking greater speed, selective breeding would likely already have brought it about.

The thoroughbred paradox

At the Belmont Stakes in 1973, Secretariat ran in a category of his own. His extraordinary performance seems to have been the result of many unlikely factors aligning. After he died, Secretariat’s heart was reportedly measured at almost 10 kilograms – twice as much as normal. This appears to have been a physiological fluke, however, as it isn’t a trait reliably passed down to offspring. Combined with his unusual stamina, exceptionally powerful legs that allowed him to cover 25 feet per stride, favorable race conditions, and a skilled jockey, this produced a race time that has still never been matched half a century later, despite advances in breeding, training, nutrition, and veterinary care.

Secretariat offers a glimpse of the upper limits of biology. But as racehorses have pushed against that limit to become faster and more powerful, their population has become more fragile as the gene pool has narrowed. Our 4,000-year pursuit of the ultimate horse may not have much further to run.

Sophie Fessl is a science journalist.

Western countries used to let landowners build almost anything anywhere. Now, strict rules freeze the character of most neighborhoods, banning change and densification. Why? One theory is that modern buildings tend to be ugly, leading residents to support rules that exclude them from their neighborhoods. If this is true, then designing beautiful buildings could lead to more development. Housing reformists have vigorously debated this theory. Many British reformists are sympathetic, whereas Australian reformists tend to be skeptical, and Americans come down on both sides.

I do believe that ugliness plays a role in hindering development, but not in quite the way usually proposed. Ugliness is probably not a major driver of opposition to development by local people. Local opponents have many other concerns that are at least as important, like disruption from construction, loss of green space, pressure on local services, and diminished social exclusivity. But there is strong circumstantial evidence that ugliness is sometimes a major driver of opposition among people who live nowhere near the development in question. The first group are often called ‘NIMBYs’, for ‘Not in my backyard’. Let us call the second group ‘NITBYs’, for ‘Not in that backyard’.

While a few NITBYs are fervent campaigners, most are only casually interested. Their motives are faint but basically altruistic: their question is whether or not, based on a cursory assessment, a development is an objective improvement to its neighborhood. In certain contexts, the ugliness of a development can summon into being a huge cloud of NITBYs, whose interest in the scheme may indeed be superficial, but who can nonetheless be collectively potent.

Subscribe now

This model is especially compelling in the case of heritage conservation. Until the 1960s, the redevelopment of historic buildings was almost always permitted; today, it is almost always banned by conservation rules. Supporters of conservationism usually portray it as a response to the destructiveness of postwar planners, while opponents see it as a pretext for suburban NIMBYism. In fact, I shall argue, neither explanation is plausible. On the one hand, postwar planners were no more destructive than the Victorians or Georgians had been: the rate of demolition was historically normal, and cannot explain the wildly unprecedented policy response. And on the other hand, there was no need for NIMBYs to invent pretexts to ban new buildings, as they had already successfully prohibited the kinds of development they disliked in the first half of the century.

What had changed, and what generated the host of NITBYs that bore conservationism to victory, was the ascendancy of modernist architecture, a style that most people demonstrably find relatively ugly. Conservationism was a reaction to postwar redevelopment, as its proponents claimed. But it was less a reaction to what the modernists destroyed, than to what they created.

Ugliness and NIMBYism

Most debates about the policy significance of ugliness presuppose a certain model of how it affects housebuilding. On this model, local people resent the prospect of having ugliness inflicted upon them, they therefore oppose ugly developments, and politicians implement antidevelopment policies to placate them. This probably does happen sometimes: ugliness obviously does affect local people, and it would be surprising if this had no effect at all on their behavior. But a closer look suggests that ugliness plays only a minor role in motivating NIMBYism.

One reason for skepticism is that the occasional beautiful developments that do get built still often encounter fevered opposition. I’On (pronounced ‘ion’) in Charleston, South Carolina is one of the loveliest neighborhoods in North America. It has grown gradually since its founding in 1995, occupying a largely empty site between several existing residential subdivisions. Despite its walkable urbanism, tree-lined streets, and exquisitely detailed houses, thousands of local people petitioned against it when first proposed. The town council initially rejected the scheme, and a tortuous legal battle was fought to downzone the site through a local referendum. The NIMBYs were defeated only after the South Carolina Supreme Court found that zoning decisions cannot be made by referendum.

Such stories continue to appear today. The present king of the United Kingdom is an architecture enthusiast, and while he was prince, he orchestrated the delivery of several unusually attractive developments in his official landholdings (which, confusingly, are called the Duchy of Cornwall), including the famous developments of Poundbury and Nansledan. The Duchy is currently proposing a third, at Faversham in Kent. Its proposals show what would be one of the most appealing urban extensions in modern Europe. Nonetheless, it has triggered hundreds of letters of protest, as well as opposition from Faversham Council, the neighboring councils, and the local Member of Parliament.

Subscribe to print

Anecdotes like these are only weak evidence, not least because it is possible that the attacks would have been even more intense if the developments had been ugly. But they do suggest that beauty is not a panacea for NIMBYism.

A more powerful reason to doubt the role of ugliness in generating NIMBYism is that it gets the timing wrong. It is true that land-use rules became far more restrictive in the twentieth century. It is also true that the dominant architectural styles became much more unpopular: visual preference surveys consistently find that most people prefer traditional styles to modernist ones. Viewed from a distance, it looks plausible that the two are causally related: new buildings became visually displeasing to most people, and as a result they started to push back against them.

In fact, however, these changes happened in the wrong order. Restrictive zoning emerged in Germany and Austria-Hungary in the 1890s and spread quickly thereafter. Italian cities began introducing zoning plans in the 1900s, Britain created a national framework for zoning in 1909, and France followed suit in 1919. Zoning spread quickly across the United States in the interwar period. The restrictiveness of early zoning varied by country, but it could be very tight: in Germany and Austria most suburbs were capped at their existing densities well before 1914, and retain those densities today.

Subscribe now

Modernist architecture began at least a generation later. It emerged in the 1920s, chiefly in Germany, and spread in the 1930s as a minority style for clients who wanted something distinctively futuristic. In the United States, its impact was particularly faint, and famous American buildings of the 1930s and 40s, such as the Supreme Court Building, the Empire State Building, and Jefferson Memorial, remained resolutely Neoclassical or Art Deco. The global triumph of modernism came only in the 1950s.

This means that the Great Downzoning happened in countries where most new buildings were still in the traditional styles dominant in the nineteenth century, with at most a minority in the novel but decorative styles we now call Art Deco. No switch towards styles perceived as ugly had yet occurred: the general picture was one of continuity with the past. The flats that were banned by early zoning would generally have had classical cornices, pedimented windows, and rusticated basements. In other words, NIMBYism triumphed long before it became true that, in most people’s eyes, the average new building was uglier than the average old one. This suggests that, though making development beautiful might palliate NIMBYism somewhat, the effect would be modest.

Perhaps this should not surprise us. After all, even the most beautiful neighborhood only emerges after several years of extreme ugliness, while the buildings are under construction. And however beautiful buildings may be, development will still have its other well-known impacts on local residents, like loss of light and green space, pressure on infrastructure and services, increase in noise, damage to social cachet, and change in the character of the neighborhood. Removing the problem of ugliness may reduce NIMBY zeal a little, but the number of NIMBYs it satisfies entirely will be small.

Was conservationism a response to modernist destructiveness?

Ugliness is clearly not the main driver of local opposition to new developments. This does not, however, mean that ugliness is irrelevant to housing shortages in the West. Today, American prohousing advocates work to generate statewide or national support for development in order to override the locals, whose representatives control the strict zoning that slows down development and makes housing scarce and expensive. Prohousing advocates have secured some important victories. But one area where they have almost invariably failed is in enabling more development in historic areas. The same is true for reformist campaigns around the world. Old buildings are protected from redevelopment across the West, even when they sit on the most valuable central land.

How did conservation become so powerful? The two most popular theories are (a) that conservation rules arose as a response to the unprecedented destructiveness of postwar planners and developers or (b) that they are a clever pretext exploited by local NIMBYs. I believe the evidence contradicts both. Instead, heritage conservation arose once most people began to feel that new buildings were uglier than old ones, generating widespread opposition to the redevelopment of old neighborhoods by people who did not even live in them.

Subscribe now

The idea of conserving built heritage was not entirely a twentieth-century invention: the artist William Morris was an early proponent of the idea, establishing the Society for the Protection of Ancient Buildings, whose aim was to prevent the overzealous ‘restoration’ of churches and other historic buildings, in 18771. Morris was considered something of an eccentric in his own time, however, and architectural conservationism did not achieve anything like the popular support it has today until much later. In 1960, most European countries protected only a tiny minority of monuments from development, and even these limited restrictions dated largely from the 1940s and 50s. In most American states, the authorities protected nothing at all. Over the next twenty years, this changed drastically. Heritage registers were created, expanded, and strengthened. ‘Historic districts’ or ‘conservation areas’ were declared. Governments halted redevelopment schemes and redirected resources towards refurbishment and restoration.

Taken together, these measures were extraordinarily successful. In Paris, plans for the city introduced in the 1950s foresaw the demolition of two thirds of Paris’s city blocks over the next few decades, the bulk of Paris’s urban fabric from the nineteenth century. In Britain, the government actually did demolish at least 1.5 million homes in slum clearance schemes in the postwar decades. This was nearly 10 percent of the overall housing stock, but since these ‘slums’ were largely eighteenth or nineteenth-century buildings, it will have equated to between fifteen and twenty percent of the prewar stock. The United States seems to have had even higher rates of (privately led) destruction, with one report finding that nearly half of the 12,000 buildings recorded in the Historic American Buildings Survey of 1933 had been demolished or seriously mutilated by the middle of the 1960s.

Subscribe to print

Conservation policy brought such demolitions almost to a standstill. In France, 1.8 percent of pre-1949 dwellings were demolished between 1999 and 2013, an annual rate of 0.13 percent. German states report even lower rates of demolition of pre-1919 buildings. In Berlin in 2022, just nine buildings from before 1919 were demolished out of a total of 50,337, a rate of 0.018 percent. In North Rhine-Westphalia in 2023, 56 pre-1919 buildings were demolished out of 445,226, a rate of 0.013 percent. At this rate, it will take North Rhine-Westphalia 7,951 years to demolish its prewar stock entirely. In Britain, government statistics show a paradoxical increase in the number of pre-1919 dwellings between 2012 and 2024, the result of more homes being subdivided than demolished. Old American buildings are demolished rather more often, partly because they are timber-framed and therefore harder to maintain in safe condition. But in the American Northeast, the annual demolition rate of pre-1920 buildings between 1997 and 2001 was still only 0.25 percent, while in the West it was slightly over 0.3 percent2. In all these countries, the old buildings that are demolished are usually decayed and neglected. Many are in deprived post-industrial towns rather than in areas with strong pressure for densification.

The standard account of this shift sees the rise of the conservation movement as a response to the unprecedented destruction of heritage by postwar developers and planners. If we take the above figures in isolation, this seems plausible. The problem is that the destructiveness of 1945–1970 was really nothing new: earlier generations had destroyed just as much of their architectural inheritance without generating corresponding resistance.

A graphic illustration of this is visible on the Rue François-Miron in Paris, where stand Paris’s last two fully intact timber-framed houses. Until the sixteenth century, almost all houses in Paris were timber-framed. In the centuries since, Paris was never annihilated by a great fire, earthquake, or bombing, unlike Chicago, London, San Francisco, and Tokyo. But its tens of thousands of timber-framed houses were demolished for redevelopment, until, by the mid-twentieth century, only these two remained. Many of their sites have since been occupied by several progressively larger buildings, demolished and replaced in sequence.

This rate of redevelopment was not unusual. London’s medieval stock was mostly destroyed in the Great Fire in 1666. But the rebuilt City of London of the late seventeenth century has also vanished. Only somewhere between 100 and 200 homes survive from this period, though more than half a million people lived in the brick-built London of 1700. Some seventeenth-century buildings were destroyed in the Second World War, but the vast majority had already been demolished and replaced in the eighteenth, nineteenth and early twentieth centuries. Assuming 100,000 homes in 1700 and two hundred survivors today, that means a destruction rate of 99.8 percent, considerably more thorough than that of the Great Fire.

This process was perhaps even more marked in the United States, where the lack of height restrictions created intense incentives for redevelopment after the invention of elevators and steel frames in the 1880s. Fewer than twenty buildings of any kind survive in New York from before 1800. Boston has perhaps fifty or a hundred. Almost all of these buildings were already gone before the rise of modernism, demolished in the nineteenth century or in the furious building activity of the Roaring Twenties.

The rate of redevelopment could be even faster for certain types of building. In the Gilded Age, Manhattan had several hundred urban palaces, huge houses of the great business dynasties. Perhaps three quarters were demolished in a remarkably short period in the late 1920s. The Cornelius Vanderbilt II House was demolished in 1926 for the Bergdorf Goodman building, a department store. The Mrs William B. Astor House was also demolished in 1926 for the Temple Emanu-El of New York, a magnificent synagogue seating a congregation of 2,500 people. The Elbridge T Gerry Mansion was demolished in 1929 and replaced by the Pierre, a skyscraper hotel in a French Renaissance style. Ironically, all three of these buildings now have heritage protection, either as individual landmarks or as elements of historic districts.

This destructiveness was not limited to the private sector, especially in Europe, where medieval and early modern city centers frequently stood in the way of government schemes. The most famous case of this was ‘road cutting’, the policy of driving new arterial roads through city centers to improve traffic circulation, which was unnecessary before the age of the car on generously gridded New World streets. Many of Europe’s most famous urban streets were originally cuttings, like Regent Street in London and the Rue de Rivoli in Paris. Although cuttings mainly served a practical function, the tree-lined boulevards they created were also seen as aesthetic improvements.

There is one interesting exception to this destructiveness: urban railways. Nineteenth-century railways generated huge clouds of steam and coal smoke, and were regarded as blights on the neighborhoods they passed through. As a consequence, there are almost no cases in which a railway was cut through a city center: this is why cities like London and Paris have a ring of railway termini around the historic core. In other words, nineteenth-century people behaved just like twentieth-century people in respect of the one kind of infrastructure they found overwhelmingly ugly, just as the anti-ugliness theory would predict.

Subscribe now

Not everyone was happy about the tearing up of the old to make way for modern capital cities. People displaced by public works were obviously upset. Some commentators also regretted the destruction of historic buildings, especially when high-status buildings like palaces were replaced by low-status buildings like apartments. On the other hand, many Georgians and Victorians thought that redevelopment generally made their cities better. Although some ancient buildings were prized, normal houses generally declined in value over time, like cars or computers today: the default assumption was that buildings degraded with use, and hence that a new replacement was probably better.

Many people also thought that architects were getting better at designing attractive buildings. In 1868, The Builder, Britain’s leading architectural magazine, proclaimed that:

The overall picture here is one of striking continuity between the modernists and their predecessors. The modernists certainly demolished a lot, but not generally more than the Victorians or Georgians. In a sense, they were much less destructive, since they were halted when they had demolished only a substantial minority of the inherited building stock, while the Victorians and Georgians merrily continued until they had torn down almost all of it. The idea that postwar planners were moved by destructive animus towards the past is mostly a myth. Their views about urban change were historically normal, and had generally been shared by the wider public. The fact that redevelopment lost the consent of the public in the 1960s and 70s requires some other explanation.

Was conservationism a pretext for NIMBYism?

If postwar destruction did not cause the conservation movement, what did? Some readers will sense an obvious answer here. Housing reformers have long suspected that the conservation movement is mostly a pretext for NIMBYism. According to this theory, NIMBYs actually oppose development in order to exclude poor people or non-white people from their neighborhoods, or to sustain high property values, or from pure reflexive dislike of change. But since none of these is a persuasive argument for state coercion, NIMBYs therefore have to invent ‘pretextual’ reasons for opposing development. According to this theory, the idea that we must conserve architectural heritage is one such pretext.

The idea that conservation is a front for some other objection can seem plausible. When I attend planning committee meetings, I often have the overwhelming impression that opponents’ arguments are heavily pretextual: people who have never shown the slightest interest in heritage, and who have perhaps gutted the historic features of their own homes, suddenly become fanatical champions of some trivial historic object when it stands in the way of a development. (Intense interest may also be discovered in bats, newts, hedgehogs, bees, blackbirds, public housing tenants, flood risk, key workers, young people, old people, and so on).

Subscribe to print

As a general explanation for the rise of conservation in the twentieth century, however, the pretextual theory is surprisingly weak. The most obvious problem is once again sequencing: the rise of NIMBYism happened long before the rise of the conservation movement. As we have seen, suburban zoning spread across much of Europe before the First World War and then across North America in the interwar period, while conservation restrictions were extremely limited before the 1940s and only really became an important constraint on development in the 1960s and 70s. Many countries thus see gaps of forty or even seventy years between the two movements. Why didn’t NIMBYs invent conservationism earlier? Why, indeed, did they bother to invent it in the 1960s, long after they had already succeeded in protecting their affluent suburbs from development using other arguments?

The pretextual theory also struggles to explain the priorities of conservationism. As their name suggests, NIMBYs care chiefly about their own backyards – that is, typically, middle-class suburbs. Conservationism certainly does sometimes protect such places, but it is not restricted to them. It also protects working-class housing, commercial downtowns, public buildings, isolated country houses, and rural churches. In fact, it has often had far more effect on these buildings than it has on suburban areas, partly because suburbs were already protected by zoning, and partly because postwar governments wanted to clear ‘slums’, not middle-class neighborhoods. In other words, the conservation movement has the priorities of a NITBY movement, not a NIMBY one.

The difference between conservationist and NIMBY priorities is starkly illustrated by the divergent trajectories of city center districts. City centers with less historic build stock have frequently seen massive densification since 1950, because they have neither beautiful buildings for NITBYs to protect nor many local residents to object on NIMBY grounds. Thus many American, Canadian and Australian cities have seen forests of skyscrapers rising in their downtowns, while their vast suburbs, full of homeowning NIMBYs, remain petrified at low densities. Urbanists write about an ‘urban transect’, with densities gradually rising towards the center. These cities have developed a distinctive ‘L transect’, sheer at the core but flat everywhere else. This is the urban form that arises where local NIMBYism is a powerful force while NITBY conservation has less relevance.

By contrast, European city centers have been more perfectly frozen than perhaps any other kind of neighborhood: the building stock of central Paris, Rome, or Madrid has hardly changed at all since 1960. When European municipalities want to develop a skyscraper district, they generally have to find a low-end suburban site for it, like Paris’s La Défense or Madrid’s AZCA. If current plans for tall buildings around the Périphérique ring road go ahead, Paris may end up with a gentle U transect, with its highest densities displaced to the periphery. The obvious reason for this is that European city centers are where historic buildings are concentrated. They have no special significance for most NIMBYs – although they have often now gentrified, many centers were poor or depopulated in the 1960s – but they are the natural focus of NITBYs’ efforts.

Subscribe now

Where European cities have densified their centers since 1945, it is generally downstream of heavy bomb damage, as in Frankfurt and London. One famous study found that the Blitz ultimately made London’s economy 10 percent larger by enabling higher densities on former bomb sites. If London’s development restrictions were solely driven by NIMBYism, this would be inexplicable: sites where density had been randomly lowered to zero in 1941–1945 would if anything be expected to have lower density today, since the NIMBYs would have been resisting densification from a lower baseline. The reason that bomb damage enabled higher subsequent densities is that development is often blocked by NITBY protection of heritage architecture, not NIMBY opposition to density.

The fight against uglification

The true explanation of the spread of conservation is before our eyes: the rise of perceived ugliness. Redevelopment in the postwar era did not become more common or more destructive of heritage. But it did become, in the view of most people, uglier. This may have made people (even) more hostile to redevelopment near them. But its politically decisive effect was to make people more hostile to many kinds of redevelopment that did not affect them personally.

Most people are not principled opponents of redevelopment as such. Even today, developments on former industrial or logistics sites are often widely popular, like NOMA in Washington DC or Coal Drops Yard in London. But many people are principled opponents of redevelopment when it seems to uglify places. Very many people dislike the idea of their city or their country becoming uglier, even when they do not live near the development in question. They lend low-level, passive support to conservationist campaigns – support which aggregates into a powerful force in a democratic society.

How did people come to expect that new buildings would be uglier than what came before? As we have seen, this view was not standard historically. There are two main causes. First, in the middle of the twentieth century, traditional architectural styles were superseded by modernism, characterized by lack of ornament, repetitive facade patterns, and the use of exposed steel and concrete. This style emerged in the 1920s and became dominant for everything except suburban housing in the 1950s. As noted above, this style is broadly unpopular with the public. Replacement of prewar buildings in traditional styles with postwar buildings in modernist ones will thus, to most people, constitute uglification. This is the main reason that redevelopment switched from being aesthetically neutral to being uglifying.

Subscribe to print

Second, at around the same time, mass car ownership became dominant. Unlike modernist architecture, cars are basically popular. But it is nonetheless obvious that, although individuals benefit from cars, spaces are degraded by heavy vehicle traffic. This is irrelevant to how people feel about some kinds of redevelopment, but it is worth mentioning because of how it affects views of street cuttings. A nineteenth-century boulevard was an airy, tree-lined space along which horse-drawn carriages flowed, roughly at walking speed. On the whole, people seem to have preferred them to narrow side streets, as contemporary property maps illustrate. By contrast, nobody prefers living near a modern highway, to the extent that the authorities often build sight and sound barriers around them.

The anti-ugliness theory of conservationism lines up strikingly with the timing of events. Developers had been demolishing vast quantities of historic stock for thousands of years with barely a whisper of conservationist resistance; then, within ten or fifteen years of the ascendancy of an architectural style that the public disliked, an immense movement to halt the replacement of old buildings appeared almost from nowhere.

This theory also explains the priorities of the conservation movement. On the one hand, as noted above, conservationists have successfully protected a much wider range of pre-1914 buildings than NIMBYs have, including in city centers and other places where NIMBYs are scarce or absent. On the other hand, conservationists have been far less effective in defending postwar modernist heritage, being either indifferent to it themselves or unable to mobilize wider public support. There do exist conservation groups defending modernist architecture, like the Twentieth Century Society in Britain, and some high-profile modernist buildings have received conservation protection. But the numbers are tiny relative to prewar architecture. In England, 300 postwar buildings had been listed as of 2003, apparently growing to about 500 in 2015, out of some 375,000 listed buildings in total. The American National Register has a blanket ‘fifty year rule’, almost never including anything built within the last half century.

It also seems to me that the anti-ugliness theory is a plausible account of the emotional character of the conservation movement. It is true that many conservationists are not explicitly anti-modernist, and that today the orthodox high-status view is to support conservationism for old architecture and modernism for new ones. I suspect, however, that conservationists were appalled by uglification, but sought to avoid direct confrontation with high-status modernism by sublimating their appreciation of beauty into appreciation of heritage. Conservationists could thus promote traditional architecture without attracting charges of pastiche-mongering. In other words, many conservationists secretly love old buildings because they are beautiful, while pretending to love them because they are old.

Subscribe to print

Ugliness and the housing shortage

How much impact does conservation have on the housing shortage? The answer is complicated. Even in the European countries with the oldest build stock, only a fifth of housing dates from before 1919, while in the United States just 6 percent does. This suggests that rules protecting old buildings would do little to prevent the construction of new ones. But because historic buildings are concentrated in city centers, and because conservation systems tend to restrict what can be done in the environs of old buildings as well as within their curtilages, their effect is much greater than the raw statistics suggest. In fact, in most European cities, centers are effectively solid phalanxes of conservation designations, with new development largely displaced to inferior sites on the urban periphery.

The impact of conservation in the United States is smaller, but still considerable. Manhattan, central Boston, and San Francisco are not under blanket conservation designations like Paris, Amsterdam, Madrid, or Rome. But large areas still fall under conservation protections, often exactly the areas where YIMBYs would most like to enable development. This means that conservation, and hence ugliness, still acts as a significant constraint on development, albeit a less important one than the general rise of suburban zoning.

Cogent arguments may be given for the redevelopment of historic neighborhoods. Densifying central areas of cities creates new housing where it is most needed, and where it contributes most to economic growth. It enables people to walk and cycle to work, or to rely on public transport. New buildings could be safer, better insulated, and more environmentally sustainable than their predecessors.

For most Westerners today, however, the prospect of destroying their cities’ historic neighborhoods remains a horrible one. People feel implicitly that we possess a finite stock of beautiful buildings, and that they are more or less irreplaceable. When one is destroyed, we lose forever a part of our inheritance, and condemn our children to live in a permanently uglier world.

So long as people feel this, they will never tolerate the large-scale destruction of historic building stock, no matter what ingenious arguments YIMBYs make for it. Their dread of ugliness will hang over our cities like a curse, freezing them in the last moment of their beauty. If that curse can be broken, it will not be by the arguments of economists and transport planners, but by confidence that change is not disfigurement, and that it will yield cities we can love.

Samuel Hughes is an editor at Works in Progress.

Artwork by Daniel Cox.

But they are far from the only medicine with more than one use. Aspirin, colchicine, minoxidil, and Viagra were all found to treat more conditions than expected, and about a third of drugs end up with a second approved use.

In this episode, Jacob and Saloni explore the idea of drug repurposing: taking a medicine made for one disease and finding it works against others. They trace how GLP-1 drugs emerged from an adorable Gila monster, why some drugs have multiple uses, why so many of those uses go untested, and how patents, competition, prizes, and platform trials shape whether we ever find them.

Hard Drugs is a podcast from Works in Progress about medical innovation, presented by Saloni Dattani and Jacob Trefethen.

You can watch or listen on YouTube, Spotify, or Apple Podcasts.

Transcript

Saloni Dattani: New weight loss drugs called GLP-1s, which include Ozempic and Mounjaro, have transformed treatment for two diseases: obesity and diabetes. They reduce high blood sugar levels, slow down the stomach’s emptying of food, and suppress appetite, which causes weight loss.

Jacob Trefethen: New research suggests they also help with other conditions, including heart disease, kidney disease, sleep apnea, and potentially even Alzheimer’s, and clinical trials are underway to test these too.

Saloni Dattani: But these aren’t the only drugs with multiple effects. Although aspirin has been used for more than a century, it was established in the 1980s that it could help treat cardiovascular disease as well. The same is true for colchicine, an ancient gout medicine that was recently found to help treat heart disease. There’s omalizumab, originally an asthma drug that, it turns out, helps treat food allergies.

Jacob Trefethen: In this episode, we’re going to talk about the multiple effects of GLP-1 drugs and the broader idea of repurposing: when you take a drug that’s used for one condition and find it works for other diseases too. What if many more drugs like these are hiding in plain sight? How do we get more of them?

Saloni Dattani: Welcome to Hard Drugs, a cool, awesome new podcast by Saloni Dattani, that’s me, and Jacob Trefethen.

Jacob Trefethen: I don’t know if we’re new anymore, Saloni.

Saloni Dattani: Oh, that’s true.

Jacob Trefethen: But it’s awesome still.

Saloni Dattani: It’s been our first birthday. We started our podcast a year ago.

Jacob Trefethen: That’s right. That’s right. Did you do anything to celebrate?

Saloni Dattani: No, I only realized a few days after.

Jacob Trefethen: That’s a classic anniversary right there, you know? We both missed it.

Saloni Dattani: Okay, so I want to start this episode by doing a little bit of trivia. There are a lot of drugs that have multiple effects, multiple uses, and I wonder how much you know about them.

Jacob Trefethen: Hmm. I’m ready. I think I’m going to, well, we’ll see. You hit me and then I’ll tell you how well I’ll do.

Saloni Dattani: I’m going to start with an easy one.

Jacob Trefethen: Oh gosh.

Saloni Dattani: I think you’ll get this one. I hope. Okay. In the early 1990s, researchers at Pfizer tested a new heart drug for angina. It turned out it did very little for chest pain, but male volunteers in the study were strangely reluctant to return their leftover pills. What was it? What did it eventually become used for medically?

Jacob Trefethen: I think I’m going to get this one. I think it’s Viagra.

Saloni Dattani: Ding, ding, ding! You’re right. It’s Viagra.

Jacob Trefethen: Yes. This one is a famous repurposing story that I’ve heard before. Yes. Viagra or Sildenafil, or I forget what the, what’s the name for Viagra?

Saloni Dattani: Yep. Sildenafil.

Jacob Trefethen: Sildenafil, sildenafil, yes. Some surprising side effects found in the clinical trial.

Saloni Dattani: So what’s the other condition that it’s used for?

Jacob Trefethen: You mean now or in the 90s?

Saloni Dattani: Yeah, like medically.

Jacob Trefethen: Oh, I see.

Saloni Dattani: I guess that’s also medically.

Jacob Trefethen: In my memories, it’s something to do with the heart and blood vessels, but I actually can’t remember.

Saloni Dattani: Yeah. That’s right. It’s hypertension, so pulmonary hypertension. It reduces the blood pressure.

Jacob Trefethen: Very good. Did the original thing it was tested for, is it used for that?

Saloni Dattani: I think the original use was angina as well, which is also related to blood pressure, but it basically acts on certain enzymes that are much more common in the lungs and the penis than in the heart or near the heart. So that’s how it works. Okay. You got that one. I have another, this one’s harder, maybe. I didn’t know this until recently. So have you heard of thalidomide?

Jacob Trefethen: I have heard of thalidomide.

Saloni Dattani: Thalidomide is an infamous drug because it was originally sold for morning sickness in Europe and many other countries. Later on, it turned out that it actually caused birth defects as well. It’s one of the worst medical scandals and led to the FDA changing its oversight on safety for new drugs. But it turns out that’s actually also a treatment for another disease. It’s used as a standard treatment for another disease today. Do you know which one?

Jacob Trefethen: This rings a bell... Oh, gosh. What is it used for? Um. Oh, God, I’m embarrassed. I can’t remember. I remember it is used, and I can’t remember what’s for.

Saloni Dattani: Maybe take a random guess.

Jacob Trefethen: Okay, random guess. Thalidomide might be used for... hair loss.

Saloni Dattani: That’s a good guess. It’s not hair loss though. It’s multiple myeloma, which is a blood cancer.

Jacob Trefethen: A little bit more serious than hair loss. The reason I should have done better test-taking skills there is the fact that thalidomide can have quite severe side effects related to the fact it’s only used for a severe disease.

Saloni Dattani: Yeah.

Jacob Trefethen: That was what we would say pretty bad guessing from a trivia participant.

Saloni Dattani: It’s also used in some cases to treat leprosy.

Jacob Trefethen: Oh, okay.

Saloni Dattani: Which I didn’t know either. But the way that it works is it tags a cancer-causing protein for destruction. That tagging and causing destruction thing is also what happens in limb development in babies. That’s how it causes birth defects as well.

All right. Third one. This one is not a single answer, but you can give as many answers as you can. It’s about Botox. Botox paralyzes muscles and it was originally discovered as a toxin, but in small and precise quantities, it can be used medically or cosmetically, for example, in reducing frown lines and wrinkles. It’s actually approved for around a dozen medical conditions in the US, and over 30 worldwide. How many of those medical conditions that Botox is used for, can you name?

Jacob Trefethen: Okay. Over a dozen?

Saloni Dattani: Around a dozen.

Jacob Trefethen: Over 30 worldwide. Okay. I think it’s frown lines between the eyebrows, number one. Frown lines on the side of your eyes, number two. I think little sort of cheeks sometimes we’ll be going for. We’re already at three. Oh, there’s left side of the face, right side of the face. We’re actually at six.

Saloni Dattani: Oh, yeah.

Jacob Trefethen: The remaining six approvals, I’m not sure. Do you want to give me some?

Saloni Dattani: Frown lines on your arms, frown lines behind your ears. Okay, no, let me name them. I think you had the right idea-

Jacob Trefethen: That’s VERY generous.

Saloni Dattani: -that it was kind of about muscular paralysis. But it’s not about frown lines. It’s used to treat crossed eyes, strabismus, and eyelid spasm, neck muscle spasm, also for preventing chronic migraine and severe underarm sweating.

Jacob Trefethen: Oh, I know that one. Yeah, I know someone.

Saloni Dattani: You knew that one? Then to treat overactive bladders and urine leakage that’s caused by neurological conditions, then also spasticity of the legs and arms. It kind of makes sense, they’re just different reasons that you would want to paralyze muscles.

Jacob Trefethen: Right. Luckily for us, we...

Saloni Dattani: You don’t have any wrinkles yet?

Jacob Trefethen: Thank you. I was waiting. My armpits so far are, doing just fine.

Saloni Dattani: Not sweating that much.

Jacob Trefethen: Well, how do you rate that? I do think that men sweat more.

Saloni Dattani: There’s probably a way to, I don’t know, collect the sweat and see how much volume of sweat.

Jacob Trefethen: Good point. Good point. Yeah. I think the thing that matters is, is it enough sweat that someone can see it on my shirt? So that’s actually, it’s a binary.

Saloni Dattani: Right. Right. That makes sense.

Jacob Trefethen: And as soon as that happens... We’re going into general anesthetic.

Saloni Dattani: I don’t actually know if people use anesthetic to- before they use Botox. I thought it was just still injection or something. I have no idea, obviously.

Jacob Trefethen: Obviously. You’re making so many YouTube watchers jealous right now.

Saloni Dattani: You’re welcome.

Jacob Trefethen: They’re like zooming in on our faces. They’re like, oh shit.

Saloni Dattani: ‘Wow, they really don’t have wrinkles.’ Last question. Out of all the small molecule drugs that the FDA has approved, roughly what proportion of them have an approval for a second medical use? How many, what proportion have been repurposed?

Jacob Trefethen: That’s a really fun question, although I think those are two different questions because you don’t need an approval for a second use. A doctor can prescribe off-label if they think it might help you even without approval. So let’s just break down the question.

Saloni Dattani: I just mean the ones that are approved for a second use.

Jacob Trefethen: Totally. I’m breaking it down in my own head. So there’s small molecules. There’s different types of drugs and therapeutics. Small molecules are, in my head, more likely to go all around the body and have effects in places you might not expect.

Saloni Dattani: Right. These aren’t hormones or peptides. They’re not vaccines or antibodies. They’re small chemicals.

Jacob Trefethen: Yeah. That’s going to increase the number here. I would say the off-label use of small molecules is probably quite a large percentage, I would guess, have doctors who at least have once prescribed it off what it was approved for.

Then in terms of how many approved for a second condition or disease, I bet that it’s going to be less than 50%, would be my guess. Because to get that approval, you often have to generate an evidence package and, are you really going to have an effect size large enough on a new condition? I bet it’ll be less than 50. Then will it be more than 10%? Yeah, I bet it will be, because these drugs go everywhere. But I bet it’s going to be between 10 and 50, so I’m going to say 20%.

Saloni Dattani: I think that was a great reasoning process. You’re pretty close. It’s about a third.

Jacob Trefethen: Wow. That’s cool.

Saloni Dattani: Yeah. Which is quite a lot.

Jacob Trefethen: Yeah.

Saloni Dattani: This is out of drugs approved between 1997 and 2020.

Jacob Trefethen: Okay.

Saloni Dattani: Yeah. About 32% have a new use approved.

Jacob Trefethen: Okay. Wow. If we run the clock for another couple decades, some of the ones in that batch will get more uses approved probably.

Saloni Dattani: Probably, yeah. Isn’t that cool?

Jacob Trefethen: That is cool.

Saloni Dattani: It’s not that uncommon for drugs to have multiple uses.

Jacob Trefethen: I think I did pretty poorly in that trivia.

Saloni Dattani: How many did you get? You got the Viagra one.

Jacob Trefethen: I got the Viagra one.

Saloni Dattani: You sort of got what it was used for.

Jacob Trefethen: Yeah, I got the gist. The thalidomide one, I recalled that it was used for something and didn’t even get close. Then the Botox one I got, I pretty much nailed that one. Okay, so maybe one for four. That’s about the same amount as drugs get repurposed.

Saloni Dattani: Very good. All right. So the most famous current drug that is being repurposed or actually has already been repurposed, I think, are GLP-1s, and so these are weight loss drugs that act on a receptor called the GLP-1 receptor. They include Ozempic and Mounjaro and a bunch of other ones that are kind of in the pipeline right now.

They’re used currently for treating both diabetes and overweight or obesity. But it seems like they might work for other conditions as well. They already have benefits for kidney disease, heart disease, sleep apnea - among people who have diabetes or obesity. But it’s possible that they also have benefits for people without diabetes or obesity. So I wonder if you can guess how that’s possible.

Jacob Trefethen: Yeah, how it’s possible there’s multiple effects, basically? Yeah, I think in general, if you’re creating a drug that intervenes in some way in a process that happens in multiple parts of the body or a process that is pretty general purpose, then you might find that you’re having effects down the line that aren’t the primary thing you were aiming at. I think that’s probably the core of the answer here. Is that fair?

Saloni Dattani: I think that’s right. There are a lot of drugs that are called ‘promiscuous’. They can act on multiple different receptors in the body, especially if they’re small molecule drugs, because they’re so small, they can get to lots of places that bigger drugs can’t. Yeah, they have lots of effects.

But also sometimes, different diseases share the same pathway, like lots of viral infections use similar viral enzymes, or lots of allergies have kind of some similar pathway. So drugs that work for some of them could work for multiple.

Then there’s also this idea that the benefit is sort of downstream. You’re treating obesity and because you’re treating obesity, it also has benefits for, let’s say, heart disease or something else. Then I think there’s a last example with a lot of mood disorders or mental health conditions where the conditions are often treated in similar ways. Antidepressants, many of them are also approved to be used for treating anxiety, for example, that might be because somehow biologically they’re related. So yeah, there are lots of different ways that you can do that. With GLP-1s, they’re not a small molecule drug. They’re peptides.

Jacob Trefethen: Well, that’s pretty close to small molecules as far as I’m-. They’re pretty small and they’re a molecule.

Saloni Dattani: Yeah, right. They’re a big molecule.

Jacob Trefethen: They’re not that-

Saloni Dattani: They’re a medium molecule.

Jacob Trefethen: Yeah, medium. I’ll take medium. I’ll take medium. But the reason I’m harping on this is because presumably the fact that they’re a peptide, not a big antibody or something like that, means that they distribute to more tissues around the body. Is that true?

Saloni Dattani: I think that’s true. Also their receptors are found all around the body. There are GLP-1 receptors in the pancreas, which release insulin and reduce glucose. Then there are GLP-1 receptors in the brain in the hypothalamus, which suppress appetite. Then there are GLP-1 receptors in the stomach, which slow down how quickly the stomach empties food into the intestines. And there’s also GLP-1 receptors in the heart and blood vessels, and probably in a bunch of other organs as well. So lots of different effects that you can have with this one type of peptide.

Yeah I think what’s interesting about GLP-1s is that a lot of people now have heard of them as weight loss drugs, but they were first used for diabetes, and they still are used for diabetes. That is pretty long, like the first GLP-1 drug, that was approved in 2005, which is pretty long ago. We have a lot of data on this and we know that it can be used for these two conditions and it’s pretty effective for them and safe.

Jacob Trefethen: I actually think the first GLP-1 drug was approved thousands of years ago. I’ve been using that stuff naturally. It just created in my body. You got any of that?

Saloni Dattani: That is true. I have that too. We all naturally have GLP-1 as a hormone in the body to reduce our appetite and reduce blood sugar levels. But the versions that are used in drugs are much longer lasting. This is what is really interesting because the GLP-1s that are used in drugs were originally discovered in a type of lizard called a Gila monster. It’s spelt G-I-L-A, but it’s pronounced ‘Heela’. There’s no G sound.

Jacob Trefethen: No G sound? Wow.

Saloni Dattani: There’s no G sound.

Jacob Trefethen: Gila monster.

Saloni Dattani: I have been pronouncing this wrong for the last two years.

Jacob Trefethen: It’s better than saying GAILA monster.

Saloni Dattani: That’s true.

Jacob Trefethen: Actually, two wrongs make a right. Maybe GAILA monster is better.

Saloni Dattani: I guess there’s no G sound because it’s Spanish. It’s found in the southwestern parts of the U.S.

Jacob Trefethen: So do you call them Hee-L-Ps?

Saloni Dattani: No.

Jacob Trefethen: You’re taking your latest HeeLP-1 agonist.

Saloni Dattani: Have you ever seen this lizard before? This Gila monster?

Jacob Trefethen: I think I have seen one picture from maybe a scientific article, but I have not met one in real life, yes.

Saloni Dattani: Me neither, which is kind of a shame because it’s really cute.

Jacob Trefethen: Is it time for a Hard Drugs expedition?

Saloni Dattani: What, to Mexico?

Jacob Trefethen: Yes, we have to meet one.

Saloni Dattani: I want to meet one. It’s quite deadly though.

Jacob Trefethen: Oh.

Saloni Dattani: We’ll come to that soon.

Jacob Trefethen: Oh.. kay. Deadly to diabetes too?

Saloni Dattani: Yes.

Jacob Trefethen: Good. That’s the goal.

Jacob Trefethen: Just remind me, so the way that this was discovered is that a patient with diabetes got bitten by a Gila monster and there were surprising effects!

Saloni Dattani: No, but that would have been a great story. Yes, but they’re found in the southwest parts of the U.S. and North Mexico, and they’re about two feet long, or one to two feet long. Pretty big for a lizard. Actually, one of the largest lizards in North America, apparently, or maybe the largest.

Jacob Trefethen: It goes with the name monster, fair enough.

Saloni Dattani: That’s true. They really do look really cute. Like if you’re listening, I would highly recommend googling them and looking at these cute lizard pictures.

Jacob Trefethen: Okay. But didn’t you just tell me they’re deadly?

Saloni Dattani: Yes. Just forget about that part.

Jacob Trefethen: Got it. Okay, great.

Saloni Dattani: I have a few more trivia questions for you. They’re more just like, fun facts, but some of them are fake. You have to guess which facts are true.

Jacob Trefethen: I’ll try and redeem myself. Hit me.

Saloni Dattani: All right. Number one, Gila monsters can detach and regrow their tail when threatened by a predator.

Jacob Trefethen: When a predator is threatening... their tail? Why would that help them? They could run faster?

Saloni Dattani: Yeah, yeah. They could run away.

Jacob Trefethen: Hmm. Let me think. I mean, that’s random. I don’t know that it would speed you up that much when they start losing balance or something. I feel like that’s so random that has to be true. I’m going to say true.

Saloni Dattani: Well, it’s actually false.

Jacob Trefethen: No!

Saloni Dattani: That’s true of some other lizards, but not Gila monsters. They actually do that. They’re just like, you’re trying to bite my tail. Well, guess what? I’ve just dropped it.

Jacob Trefethen: Honestly, the predator probably likes that too. Tasty tail.

Saloni Dattani: That makes sense. But I think they’re probably quite disappointed. Wait, what? Your tail just dropped off!

Jacob Trefethen: It is kind of like an ultimate gag. It’s like Arrested Development with the guy with the arm that is trying to teach them a lesson.

Saloni Dattani: I watched this so long ago that I don’t remember.

Jacob Trefethen: George Sr. hires his friend who has a detachable arm to teach his children lessons because the arm comes off.

Saloni Dattani: Wow. I would love that.

Jacob Trefethen: Yeah.

Saloni Dattani: Okay. Here’s the second fact. I think I gave this away a little bit. Okay.

Jacob Trefethen: Finally one I’ll get right.

Saloni Dattani: The Gila monster is sluggish in nature so it is not generally dangerous and very rarely poses a real threat to humans.

Jacob Trefethen: Okay. I think this might be a little of column A, a little of column B. I think it is dangerous to humans because of maybe venom would be my guess. But maybe that is compatible with it being sluggish. I sort of do think of it as sluggish. I think maybe... Yeah, I’m going to go with sluggish, but deadly.

Saloni Dattani: You just have a stereotype in your mind that it’s like, oh my God, it’s so slow.

Jacob Trefethen: Yeah, basically. I definitely think of it as lounging. Do you know what I mean? It’s not like one of those geckos. We’re talking a monster. It’s lounging. It’s baking in the sun. That’s the kind of energy.

Saloni Dattani: You are exactly right.

Jacob Trefethen: Oh, finally.

Saloni Dattani: It is a very slow lizard. Its top speed is about one and a half miles per hour.

Jacob Trefethen: You’re kidding. That can’t be-

Saloni Dattani: Can you imagine being that slow?

Jacob Trefethen: That is really embarrassing for the Gila monster. Wow, I kind of feel... I really changed my perspective on the Gila. That’s also... Who measured that?

Saloni Dattani: They were in a little race. They were like, oh, wow.

Jacob Trefethen: I guess you would put some prey in front of it that it wants and then see how fast it could go after.

Saloni Dattani: Maybe they’ve just been videotaping it for a really long time and seeing how fast it usually goes. But you were right, so its venom is very poisonous, its bite is excruciating. But they just don’t encounter humans that much, so they’re not very...

Jacob Trefethen: Who are they mainly biting then?

Saloni Dattani: I guess its food, usually it eats small animals like mice.

Jacob Trefethen: Right.

Saloni Dattani: And little birds, I guess.

Jacob Trefethen: It’s kind of interesting because I feel like it’s kind of like Tom and Jerry, but if Tom couldn’t run. It’s surprising, but anyway, okay.

Saloni Dattani: Okay. Next one. The Gila monster has very muscular jaws that produce a firm, tenacious bite with the venom dripping into the wound as the lizard chews.

Jacob Trefethen: Oh my God. And so is that true or false, basically?

Saloni Dattani: Yeah.

Jacob Trefethen: Okay. I think that’s true.

Saloni Dattani: That is true. Pretty terrifying.

Jacob Trefethen: Oh God.

Saloni Dattani: That is the exact description that I found in a paper.

Jacob Trefethen: Okay. Delightful.

Saloni Dattani: Sounds quite horrible. Okay, last one. Gila monsters spend most of their life underground and can survive eating only a few meals per year. True or false?

Jacob Trefethen: That is going to be true because that and that’s really going to be related to, I think that’s going to be related to Hee-LP.

Saloni Dattani: Yes, it is. It is true. They stay underground most of the year. They come up overground only during the spring, usually. And they can survive eating only a few meals per year. They’re really good at fasting. I was wondering if you could only eat three meals per year, what would those three meals be?

Jacob Trefethen: I have a sort of tradition I’ve lapsed that I, a few years ago, very much valued, which was having pancakes the night before Thanksgiving. I’d probably keep that one then. Okay. I’ve got two left. You have to really be eating the most calorie dense thing... No, I guess I’m taking that too seriously. We’re going to die in this example.

Saloni Dattani: Oh no!

Jacob Trefethen: No, no, no. Two more. Maybe, well, I have always been a sucker for cornbread. I would have a meal that was very cornbread forward. Right.

Saloni Dattani: Pancakes, cornbread.

Jacob Trefethen: Yeah. Everything’s yellow. That’s the theme.

Saloni Dattani: Potato?

Jacob Trefethen: No, the third would be a delicious salad, actually, Saloni. Oh. You got a problem with that?

Saloni Dattani: I find this hard to believe.

Jacob Trefethen: What’s your answer then?

Saloni Dattani: Potatoes. Potatoes and potatoes.

Jacob Trefethen: All three? Oh, no. I didn’t know that about you.

Saloni Dattani: I heard that potatoes contain all the nutrients that you need.

Jacob Trefethen: That’s right. That’s why I make sure to avoid other foods.

Saloni Dattani: What’s interesting about the Gila monster is that they also, they eat very large meals. They eat just like entire quail eggs at once and stuff, and they store fat in their tails.

Jacob Trefethen: Oh, their non-detachable tails.

Saloni Dattani: Yes. If they were detachable, they actually would be yum for predators to eat.

Jacob Trefethen: Okay.

Saloni Dattani: Separately, I wonder if you’ve ever wondered how venoms work. It’s not that common for lizards to be venomous and Gila monsters are venomous. I hadn’t really thought about what makes venom actually deadly to people.

Jacob Trefethen: Yes, I, um... I have looked into this a bit in my previous day job, and there’s a multitude of ways they can, is what I remember. But messing with your blood is a classic sort of vector of destruction. But is there a more... Do you have a list of destruction methods?

Saloni Dattani: What makes venom venomous? The answer is you can either use your venom to destroy red blood cells, or wreck clotting mechanisms so you cause lots of internal bleeding. The one that I had thought about was like being a nerve agent, disrupting nerve signaling, causing paralysis.

Jacob Trefethen: Yeah, yeah, yeah, definitely.

Saloni Dattani: Then some venoms digest cell membranes and connective tissue, and that spreads the rest of the venom even further.

Jacob Trefethen: Wonderful... So if anyone wants to lose weight, then...

Saloni Dattani: Let’s talk about medicines instead.

Jacob Trefethen: GLP-1s, how does this relate to GLP-1s, Saloni?

Saloni Dattani: Yeah, how does this relate to GLP-1s? What are GLP-1s? They are a type of gut hormone that is released when you eat, naturally. They’re a type of gut hormone called an incretin, and those hormones tell the pancreas to release insulin. In the 1980s, people found a natural incretin, which they called GLP-1.

But what’s sad about natural GLP-1 is that it has a really short half-life. It only lasts about two minutes in the body. That’s not very useful medically. The reason for that is that it just gets destroyed by enzymes and removed by the kidneys. So scientists were looking at this two minute long hormone and they thought maybe there’s a better version of this that we could make that we could use as a treatment for diabetes. If you can stimulate insulin production, you can treat diabetes.

There were a bunch of scientists who were trying to study that, but also trying to study this Gila monster, the lizard, for other reasons. The story here, I feel like, is kind of different from what I had heard about this. I feel like I had heard several times that GLP-1s were discovered accidentally. People were studying this lizard and then somehow it produced this hormone that was really helpful and was a source of GLP-1 drugs. But when I looked into it, it turned out that it wasn’t very accidental at all.

Jacob Trefethen: Oh, as in the Gila monsters were planning this the whole time?

Saloni Dattani: Yes, that’s exactly what I meant.

Jacob Trefethen: I knew it!

Saloni Dattani: The Gila monsters were actually- the scientists took off their masks and it turned out...

Jacob Trefethen: That is, it actually does all make sense now. The scientists were- The way they found out was they were walking at 1.5 miles an hour. Oh, sorry, sprinting.

Saloni Dattani: The other scientists were like, why are they so slow? There must be something special about them.

Jacob Trefethen: If it’s not accidental discovery, so what happened?

Saloni Dattani: There were two scientists studying these lizards for different reasons. One scientist was an endocrinologist who was interested in the venom and the fact that if people were bitten by this venomous lizard, the Gila monster, they often developed this extreme pancreatic reaction to it. It somehow stimulated the pancreas so maybe it’s involved in doing something to pancreatic hormones.

Then there was another scientist called John Eng who was studying peptide hormones in animals. He had already studied a beaded lizard’s venom and found a hormone that resembled human GLP-1. Then he turned to study the venom of another lizard, Gila monster, to find out whether it had a hormone like that too. That’s why they were studying the venom of this lizard, the Gila monster.

Jacob Trefethen: So are you telling me the venom is circulating through its veins and keeping it skinny?

Saloni Dattani: Yeah, that’s a good point. I don’t know why this hormone is in its venom. That part is surprising.

Jacob Trefethen: Yeah.

Saloni Dattani: Okay. Maybe venom is just a mix of random stuff.

Jacob Trefethen: Yeah. Yeah. Maybe. Okay. Interesting. Were they collaborating or were they working at cross purposes?

Saloni Dattani: Yeah. They were working together. Okay, so they were interested in this lizard for these two different reasons and decided to look at what was in the Gila monster’s venom and they found a bunch of peptides, and one of them turned out to be really similar to GLP-1, the natural gut hormone. It was called Exendin-4. Sounds like a villain from a cartoon I would have watched when I was five years old.

Jacob Trefethen: Did they get to name it that villain or was it already named?

Saloni Dattani: I think they named it.

Jacob Trefethen: Maybe they were watching the same cartoons as you.

Saloni Dattani: Probably. They found this other hormone that was similar to GLP-1 in the Gila monster’s venom. It also switched on the same GLP-1 receptor, so this was all in 1992. But what was even more cool about this version of the hormone in the Gila monster was that unlike natural GLP-1s in humans, which only last a few minutes, this hormone lasts hours. That makes it much more useful as a drug. The reason for that is just it contains a slightly different amino acid at the place where the enzyme was breaking down natural GLP-1, so it doesn’t get degraded as much.

Jacob Trefethen: But overall, they look pretty similar?

Saloni Dattani: Yeah.

Jacob Trefethen: Yeah. Okay.

Saloni Dattani: I guess what also I found kind of interesting was how long it took between when they discovered this Exendin-4, this Gila monster GLP-1, and how long it took from that to developing it into a drug. It was first approved for diabetes in 2005, which is really like 13 years later, which seemed pretty long to me. Apparently John Eng, who discovered it, patented it pretty quickly and presented his findings to a bunch of pharma companies but some people just thought the idea was too weird and they just didn’t see like a commercial use for it.

Jacob Trefethen: People.

Saloni Dattani: ‘What do you mean it’s too weird? It’s just a lizard!’

Jacob Trefethen: He’s walking around with his vial like, ‘There’s nothing weird about this!’

Saloni Dattani: Yeah, but that changed in San Francisco, which is where you are, at the 1996 American Diabetes Association conference, where scientists from a biotech company called Amylin Pharmaceuticals-

Jacob Trefethen: Yes, Amylin!

Saloni Dattani: were interested in this and they decided to license his patent. Then they turned it into a drug. The drug is called Exenatide. It’s a synthetic version. They’re not actually extracting it from the lizard each time. That was the first GLP-1 drug that was approved.

Jacob Trefethen: That’s great. I’m glad we got our first one. But exenatide is not what we all talk about now, so...

Saloni Dattani: Maybe we should be talking about it.

Jacob Trefethen: Maybe we should be talking about it. Exenatide in the armpits. That sounds like it was a great beginning, but how does it relate to other GLP-1s? What’s the story?

Saloni Dattani: Yeah, the other GLP-1 drugs are basically modifications of that first one. After Exenatide, the first GLP-1 drug was developed, scientists at Novo Nordisk tried to tweak it and they turned it into a longer lasting drug called liraglutide.

The way that is tweaked is basically it has like a fatty acid chain attached to the molecule, to the peptide, and that means that it can bind to albumin in the blood. Albumin is a protein in the blood that just carries around lots of different things. It’s basically like a little bus that’s going around your body and it’s like, hey, get on the bus and then the little hormones get on the bus and then eventually they get off the bus. Liraglutide can last a day versus exenatide, which could last hours. This was another advance.

Then after that, there was semaglutide, which was modified even more to last about a week. It just had a stronger fatty acid chain that grips onto the albumin more tightly.

Jacob Trefethen: We basically have this original insight starting in 1992 from the Gila monsters. Then that insight is built on to its first pharmacological point in ‘96 and onwards, and then we’re iterating, iterating, iterating off of this idea.

Saloni Dattani: Yes, exactly. You’ve probably heard of tirzepatide and retatrutide as well.

Jacob Trefethen: I have. Yes, retatrutide, yes.

Saloni Dattani: Retatrutide. What’s so interesting about these is that now it’s not just that they act on the GLP-1 receptor, they actually act on multiple receptors. Tirzepatide, which is by Eli Lilly, or it’s called Mounjaro, that acts on both GLP-1 receptors and GIP receptors. Then there’s retatrutide, which acts on GLP-1s, GIP and glucagon.

Jacob Trefethen: Boom, boom, boom, triple!

Saloni Dattani: The way that it does that is all of these receptors are evolutionarily related to each other and they look kind of similar. So you can design, you can just slightly tweak a drug so that it fits into multiple receptors and not just one.

Jacob Trefethen: It’s sort of fascinating to think about that because this is one molecule doing three things. It’s kind of like, why, why, why not have three molecules? If you ask a drug developer, a medicinal chemist, I think the answer you’ll get is, well, you can control better the dosing. You kind of want one. But it’s all over your body and randomly interacting with all sorts of things all over it. You’re making this statistical bet of how much you will interact with the three different things.

Saloni Dattani: Yeah, I think there’s like another layer of that though, because even GLP-1 receptors, on their own, they’re present in multiple parts of the body. Sometimes it helps to have a really specific drug that only attaches to one thing. Sometimes it’s better if they act on multiple things - then they could have multiple benefits.

Jacob Trefethen: Now, I live in San Francisco and I was recently at a conference where a British person was, I was talking to a British person who was visiting about science and he immediately, well, he from context got that despite the fact I grew up in England, I now live in San Francisco. So he said, oh, probably you have to leave soon so you can go buy your peptides on a street corner.

I thought, that’s a bit rude. He’s telling me that I have to go buy peptides on a street corner. Then I thought, this man, he’s stereotyping San Franciscans. Then I sort of ran through my head and I thought, well, I do have a lot of friends who have bought peptides if not on a street corner, then from an apartment.

The most common one that I have seen is retatrutide. This is not approved yet, but it’s going through the process of the FDA. But the data looks so strong that to the San Franciscan mind, you want to be getting illegal imported versions of it as soon as you possibly can, stirring them up in your fridge and then jamming yourself. Yeah, around here it’s actually called Rita. People don’t even say retatrutide.

Saloni Dattani: Rita like Rita Hayworth.

Jacob Trefethen: Yes, exactly.

Saloni Dattani: Just like her.

Jacob Trefethen: Just like her.

Saloni Dattani: I find it also, yeah, I find it interesting, the new GLP-1 drugs, they’re more effective partly through working on multiple receptors. They act on more receptors than the previous ones did, and they’re more effective probably because of that.

Jacob Trefethen: What fourth and fifth receptor would you add?

Saloni Dattani: Oh, I don’t- I think I would stop there. Honestly, that’s enough.

Jacob Trefethen: At some point, it gets so effective. It’s like, the serious point is that all of these things come with trade-offs. If you’re hitting more things, that might dial up your efficacy depending on what you’re trying to measure. But also it adds risk. You’re hitting things you might not want to or that have some function that is beneficial or keeping your body normal. Most things in the body happen for a reason. There is a genuine trade-off. You might not want to add a fifth or a sixth. I do find it funny that we now kind of have GLP-1 and then it feels like GLP-2, GLP-3. It feels like GLP-3. We’ve got to get to 5.5.

Saloni Dattani: I think I remember reading that one of the most common reasons that people dropped out of the clinical trial for it was that they lost too much weight.

Jacob Trefethen: Totally. Yeah.

Saloni Dattani: Yeah. It’s pretty high. Retatrutide in its phase three trial caused a 28% reduction in body weight. It’s huge.

Jacob Trefethen: It’s absolutely crazy. That is crazy. And that happened over the course of one day.

Saloni Dattani: What? No, it didn’t. It’s more like a year and a half.

Jacob Trefethen: I don’t even think I tricked you with that one, I think.

Saloni Dattani: I’m very used to this because when I was growing up, my brother used to just make up things and he’d say things that sounded plausible. It wouldn’t be like in the context of like, oh, do you believe or whatever. You would just say things that were false. He’d be like, ha, you believed that!

Jacob Trefethen: It’s a trick with no upside.

Saloni Dattani: That’s why I’ve turned into a really skeptical person now. I just don’t believe anyone at all.

Jacob Trefethen: Aww. No, that’s not true. You believe.

Saloni Dattani: That’s true. I thought you were right about the tapeworm being called a tapeworm because it was sticky underneath.

Jacob Trefethen: I now have to read to the audience, totally unrelatedly, the most Saloni text I’ve ever read.

Saloni Dattani: Oh, what was it?

Jacob Trefethen: About what you can believe and what you can’t believe. Let me pull it up. Someone on the internet posted a chart and we’re in a group chat together with some people who read charts and look at charts. Someone asked, “any takes on this?” Basically on this chart, how would you evaluate it?

Saloni responded, “I find it so odd for someone to tweet out something like that without even looking up the data quality notes.” I don’t know that anyone else would find that odd. “I just can’t imagine someone tweeting something without reading the appendix first!”

Saloni Dattani: I realized just after posting that, I was like, wait a second, I’m probably the only person who does that.

Jacob Trefethen: “I just find it so odd.”

Saloni Dattani: It’s very annoying when people do that.

Jacob Trefethen: No, I am with you. Anyway, so-

Saloni Dattani: Thank you. GLP-1s. We know that they’re useful for weight loss. Retatrutide, the latest one, causes a 28% reduction. That compares to semaglutide, the first one, which was about 15% weight loss. Tirzepatide, which was about 21% at the top dose. These are getting a lot more. This is crazy. I do think that it’s non-linear and that eventually we won’t be able to just keep increasing how much weight loss you can achieve with new drugs.

Jacob Trefethen: I hope so. Some of the weight is your organs, some of the weight is your nose, your teeth. Yeah. It’s worth saying this is... It’s not like, once you go off the drugs, you, most people start gaining weight again. It’s not like a permanent in your body forever kind of thing. But yeah, these graphs are really quite, quite something. It’s only 18 months. It’s not very long time.

Saloni Dattani: It’s much larger than I, I think that what’s interesting to me is that I remember in maybe 2021 or so, I was trying to find someone to write an article for us at Works in Progress about weight loss drugs. I remembered learning in my undergrad that there were a lot of failures in the 1970s, 80s, 90s, people trying to develop obesity medications and a lot of them were really toxic. Or they just caused weight loss in a really unpleasant way.

I was interested in like, what’s the state of that research now? Are there new drugs that are in the pipeline today? I asked this nutrition researcher called Stephan Guyenet to write an article about that for us. He wrote one on the future of weight loss, basically these GLP-1 drugs that hadn’t been, that hadn’t reached the finish line at that point, but it was so interesting even then to just see like how much happened in the meantime.

There was this period of maybe two decades where it seemed like a lot of pharma companies were pretty afraid to touch obesity as a potential area. Now it’s the biggest or one of the biggest areas for new pharmaceutical drugs.

Jacob Trefethen: Yeah. How much can change.

Saloni Dattani: So much can change. I also, I think that. Yeah. People often don’t know that these are also treatments for diabetes. I wonder if you know how they work at doing that.

Jacob Trefethen: I think of them originally for diabetes, or at least type 2. I believe they lower your blood sugar levels. But more specifically, let’s see...

Saloni Dattani: Yeah. I think you’ve kind of got it, but there’s an additional piece of evidence there that they don’t just reduce blood sugar level on the whole, but they reduce blood sugar level when the blood sugar levels are high.

Jacob Trefethen: Yeah, yeah, yes. Right. Right.

Saloni Dattani: It’s like a glucose dependent effect. What’s good about that is that a lot of previous diabetes drugs just generally reduced blood sugar levels. If you are on a high dose, then you could suffer from hypoglycemia, you could have really low blood sugar levels and that would be bad. But this doesn’t happen with GLP-1 drugs. They only reduce blood sugar levels when they’re high.

Jacob Trefethen: Although you have to watch out for it, right? But it’s not a big problem, it seems.

Saloni Dattani: Right. Also, unlike some other diabetes drugs, they cause weight loss instead of weight gain. There were a bunch of other diabetes drugs that did that, which is probably not great because a lot of people with diabetes are also overweight or obese. This is helpful because it tackles both things. I wonder if you know how- they’ve also been used to prevent the development of diabetes, so in people who have pre-diabetes but don’t have actual full-blown diabetes yet, how much it reduces that progression?

Jacob Trefethen: Hmm. I wonder how you measure that because prediabetes is set at a debatable binary cutoff point. Do you measure it against a continuous variable?

Saloni Dattani: This is, so both of them are measured in part based on HbA1c, which is a measure of how much sugar is attached to your hemoglobin. At a certain threshold, you can be considered having pre-diabetes. Then if it’s above that level, it’s considered diabetes. The question is, if you are in this range where you have pre-diabetes, how much does it reduce your chances of eventually developing diabetes?

Jacob Trefethen: Yeah. I don’t know the number, but my impression is a lot. I think it’s a very effective way on it.

Saloni Dattani: It is very effective. There is a trial recently called the SURMOUNT-1 trial where they gave tirzepatide, that’s Mounjaro, to people with obesity and prediabetes. They had a 94% reduction in the progression to type 2 diabetes.

Jacob Trefethen: Wow. Over what period? I’m trying to make sense.

Saloni Dattani: Over three years.

Jacob Trefethen: Okay. Basically over a three-year period, if you have prediabetes, there’s some chance you’ll progress. For people on the drug, it was like basically no chance you’ll progress.

Saloni Dattani: Right. It was like 18% or so chance of progressing in the next three years if you were on a placebo.

Jacob Trefethen: Got it.

Saloni Dattani: But if you’re on tirzepatide, it’s like 2%.

Jacob Trefethen: Oh, wow. That is amazing. Wow. That’s awesome.

Saloni Dattani: We talked about how GLP-1 drugs are used for diabetes and obesity, but they’re also being studied for lots of other diseases, like kidney disease, cardiovascular disease, sleep apnea, and also diseases like Alzheimer’s and Parkinson’s. Most of those trials are being studied in people who are already diabetic or obese and the trials are looking at whether it also improves those other conditions that they have.

With the two exceptions of the two brain diseases, brain conditions. So in the Parkinson’s and Alzheimer’s trials, GLP-1s were tested in people without diabetes or obesity. But so far those trials have found null results. They haven’t been demonstrated to be effective.

I think there’s like an ongoing debate around, does it have all of these multiple benefits because it’s actually effective for those conditions? Or is it just because it’s reducing weight and improving blood sugar levels, which usually have all of these other negative consequences? So if you reduce weight, you’re going to reduce your kidney disease or heart disease as well. I think that’s still an active debate. I wonder what you think. Would you guess that if GLP-1 drugs were tested in people who are not diabetic, who are not obese, would they still have those benefits as well?

Jacob Trefethen: Ooh, depends on the benefits, depends on the people is my scapegoat answer. My guess is that there’s stuff going on that will benefit people who are not diabetic and not overweight. Yes, yes. Now, it was disappointing to see the Alzheimer’s result that came back null. I think that could still go both ways though. That trial enrolled people who already had essentially-

Saloni Dattani: Early onset.

Jacob Trefethen: Yeah. Not early onset, but early Alzheimer’s, I believe. You can tell me if I’m right. I think it was.

Saloni Dattani: No, you’re right. Early stage Alzheimer’s.

Jacob Trefethen: Early stage. Yeah.

Saloni Dattani: So it didn’t slow that down.

Jacob Trefethen: It didn’t slow that down, but that’s- the inclusion of one of the inclusion conditions to be in that trial was that you already had confirmed amyloid in the brain, or something that would signal you probably have amyloid in the brain. So I think there’s almost a separate question of, the average age of people in that trial is probably 71 or something.

If you gave people- if people were on GLP-1s preventively much earlier, before amyloid and tau had accumulated or got that far into accumulating, could you have a preventive effect? I’m actually sort of hopeful, and my read is that the jury is still out there and there may be some benefit on Alzheimer’s that’s earlier prevention. But yeah, the data... It’s pretty clear from that trial that the hope of something that as soon as you get a diagnosis, you go on that then helps, it’s not going to be as magical as that.

Saloni Dattani: Yeah, that’s a shame. I hope you’re right that it is effective for that. I feel like when I read about these for the first time, I thought, well, some types of dementias are actually caused by cardiovascular problems, like vascular dementia. I sort of thought, maybe they’ll find a benefit in this trial, if not for any other reason, for that reason. But I think people with Alzheimer’s also having vascular dementia is not that common, but also it seems like it didn’t help in that sense. Or maybe it wasn’t powered enough to find that.

Jacob Trefethen: Right, yup.

Saloni Dattani: Yeah, I think with the other conditions like kidney disease, cardiovascular disease, at least with cardiovascular disease, my guess would be probably it does help with that in part because GLP-1 receptors are also found on blood vessels and they reduce blood pressure slightly. But also I think with lots of these conditions, it’s not really like a binary of overweight or obesity or not. Right? Like it’s continuous. I’m sure that, okay, if it helps a lot for people who are obese, it probably helps as well for people who are not to a lesser extent.

Jacob Trefethen: Yep. Then, there’s, of course, as with everything in biology, you go to the other extreme and you can harm people. If you’re prone to anorexia, if you’re, if you have low body mass, there’s ways you, but these, these things can do harm too.

Saloni Dattani: Right. I was interested in this as well because I was thinking, okay, so we have now really effective drugs that help with weight loss. What about drugs that help with weight gain? Because there are some conditions where maybe someone who has chemotherapy or something and has lost a lot of weight because of that, are there any drugs in the pipeline that help them gain weight... aside from marijuana?

Jacob Trefethen: Oh, yes. Good point. Marijuana. The pathway there goes via Taco Bell, actually, at the end. No, if you are severely malnourished, then you can get prescribed Plumpy Nut or other forms of ready-to-use therapeutic food. Therapeutic food in the sense of they are treated as medicines in some sense. Yes, there at the very least is high fat, high protein food that you do get prescribed if you’re severely malnourished. Probably not the answer you’re looking for, you probably want something more biochemical than that.

Saloni Dattani: Yeah. There are apparently a bunch of drugs in the pipeline right now that are for weight gain. There’s an antibody treatment called ponsegromab, which seems to help with weight gain, but it’s in phase three trials right now. I haven’t tried it.

Jacob Trefethen: You’re making me run through the list in my head now. There’s other appetite suppressant, stimulants have often been weight loss drugs either off-label. Are there things that off-label everyone knows you gain weight if you eat? Yeah, there are a bunch of those probably.

Saloni Dattani: That’s right. Aren’t there antipsychotic drugs that make people gain weight?

Jacob Trefethen: Yep.

Saloni Dattani: Huh, interesting. Might try one. I’m kidding. But I guess the last thing to say about GLP-1 drugs is that this is not the end. There are a lot more in the pipeline. There are new drugs being developed that don’t just cause complete weight loss through both fat and muscle, but there are new drugs that are muscle-preserving, weight loss reduction drugs. There are also different types of actual dosing or different durations of these drugs. There are people developing patches like a needle patch that you put on your arm and that slowly gets released into your body.

There’s also, recently, there’s a small molecule drug version of a GLP-1 agonist. I wonder if you know, or remember, what that’s called? It has a really funny name.

Jacob Trefethen: Oh, oh, do you mean the, the oral one? Wait.

Saloni Dattani: Yeah. Yeah.

Jacob Trefethen: Okay. Gosh, yeah, what is that?

Saloni Dattani: It’s a pill. It’s a small molecule. It activates GLP-1 receptors.

Jacob Trefethen: Gosh, I can’t remember. I can’t remember. What’s it called?

Saloni Dattani: It’s called orforglipron.

Jacob Trefethen: Yeah, they really have run out of names for Pokémon these days, reaching the bottom of the barrel.

Saloni Dattani: I usually imagine a cat typing on the keyboard and that’s how these drugs are named. That’s the end of that. GLP-1 drugs have two uses already, diabetes and obesity. They’re being tested for a bunch of other uses as well.

They were originally developed by finding GLP-1 peptides in Gila monster, a type of lizard, in their venom. That hormone was much longer lasting than the natural GLP-1 that we have in our body. By tweaking that hormone, scientists made sure that it lasted longer, even longer, in the body for days or weeks. That has led us to the drugs that we have today.

Jacob Trefethen: It’s an amazing story. I wish it could have happened quicker, as is often the case with some of the stories on our episodes, but not so bad. These drugs will go on to prevent millions of people from earlier death. Even aside from the health gains that a lot of people are going to see, there’s... these are really big population-wide effects at this point. It’s kind of wild to have something that is so new that will be so impactful.

Saloni Dattani: That reminds me that with some of these drugs, they’ve also been tested for how much they reduce mortality rates overall. The first, well, the second GLP-1 drug, liraglutide, the FDA said with any new weight loss drug, it has to be tested for how safe it is for cardiovascular disease as well. They did trials to find out how effective, how safe it was. They actually found that it reduced heart attacks in that population and it reduced mortality rates on the whole by about 12% in people with obesity, which is actually quite large. Like that’s, roughly, that’s roughly the effect of, statins in reducing mortality rates as well. And that was for the earlier GLP-1 drug so I’m guessing these new ones have a slightly larger effect.

Saloni Dattani: Okay so GLP-1 drugs are a type of drug that have multiple effect. I’m going to raise a potentially controversial or surprising opinion, which is that what if there are lots of other drugs that can do things like this too?

Jacob Trefethen: Dun-dun-DUN! I don’t think it’s possible.

Saloni Dattani: You don’t think it’s possible.

Jacob Trefethen: No, I’m joking. What’s my real answer? I sort of am a bit of a conspiracy theorist on this. Often the most powerful drugs are doing something that’s quite important. Yes, I think that sometimes-

Saloni Dattani: Yes, that seems circular, though.

Jacob Trefethen: Let me rephrase it. Some of the most important functions in the body are sort of these pathways that have many different downstream effects. If you’re targeting an important node, for sure there might be repurposed things that could happen. The thing is that most people are mostly healthy most of the time. You don’t want to be messing with those important panels.

The GLP one story is so shocking because it’s like, wait, hold on, we could have just done that the whole time? Like if we’d evolved different GLP? That’s crazy. Because usually if you’re hitting a channel like that, there’s something bad happening somewhere else. This has been a big problem in Alzheimer’s, for example. The genes and proteins that are involved in the development of Alzheimer’s, there’s more and more knowledge about them every decade. A lot of the problem is happening in the brain, but those genes and proteins are doing things all over the body. So if you try and give someone a drug that is going to interfere with them, you may end up causing issues. This happened with BACE1 inhibitors. This happened with gamma secretase.

Saloni Dattani: What’s a BACE1 inhibitor?

Jacob Trefethen: B-A-C-E-1. It’s just a class of drugs that people have tried for Alzheimer’s. The off-target effects really get you. This kind of principle, if you go to something really important and it will have lots of effects is good and bad, but true.

Saloni Dattani: Right. I wonder if you remember, so we talked at the start of the episode about some examples of drugs that have multiple uses, but how many other ones can you name?

Jacob Trefethen: Oh, okay. That’s a fun prompt. Let’s see. So there’s... maybe I’ll try and get to three and then stop. Well, there are things that you would use in different contexts for different patients. I don’t know if that counts. Like low dose aspirin for different, if you are pregnant and meet certain conditions can be useful, but that’s not the main way you would think about aspirin. Or, lithium is one that we are looking into right now, actually, for Alzheimer’s, again. Is there an effect of lithium orotate on Alzheimer’s? Not on, lithium is often used for others.

Saloni Dattani: It’s usually bipolar, right?

Jacob Trefethen: Yes. Lithium carbonate is used for bipolar. Let’s see, what’s the third fun one? How about, oh, BCG. This one always blows my mind.

Saloni Dattani: Is it actually used for those yet? I think it’s still unclear.

Jacob Trefethen: For what? BCG is used for bladder cancer.

Saloni Dattani: Really? I didn’t know that.

Jacob Trefethen: Yeah, yeah, yeah. BCG is-

Saloni Dattani: The vaccine.

Jacob Trefethen: -covered in previous episodes and you should, listeners should go back and listen to every single one in case it pops up. It is a sort of wondrous vaccine from 1921 that is still used, it’s that good, against TB. It is producing some sort of non-specific immune response in that it’s not just helping with TB, it’s helping with other stuff too. One of the things that it’s now used for is bladder cancer. People have tried it out for a bunch of different stuff too, due to this kind of non-specific effect. Do you ever want to just jack up your immune system to achieve some other goal? Yeah, BCG is a fave.

Saloni Dattani: Nice. I was thinking of SGLT2 inhibitors.

Jacob Trefethen: Nerd! Loser!

Saloni Dattani: Sorry, yeah, these are kind of similar...

Jacob Trefethen: Wait, listeners, do you not think about SGLT2 inhibitors?

Saloni Dattani: I think about them every day. I think this is the original, wow, does this just work for everything? Where they were originally developed for diabetes, but it turned out later on that they also could treat heart failure and chronic kidney disease and maybe some other conditions as well. Then you mentioned aspirin, a painkiller, but also use sometimes in pregnancy and also is a heart disease drug. That was only found out, I think, in the 1980s. Have you heard of colchicine?

Jacob Trefethen: Colchicine rings a bell, but what is it?

Saloni Dattani: It’s a gout medicine. I think in the last 15 years or so, it turned out to be pretty effective against heart disease as well. Then there’s minoxidil. Have you heard of that?

Jacob Trefethen: Any man my age has heard of that, Saloni.

Saloni Dattani: That was originally an antihypertension drug, but it later turned out to be somewhat effective as a topical treatment for baldness. Why I remembered it this year was that there was a phase three trial this year with a different formulation of minoxidil, which is longer lasting and that led to hair regrowth that was much more than the previous version. I think the previous version was like, you would have to apply it every day or something. Whereas this one, it’s a pill.

Jacob Trefethen: Yep. I, you know, just talking to friends, of course, the issue with applying it every day is like, oh God, so do I do it before a shower, after a shower? It’s kind of annoying. You can’t, there’s a pill version, finasteride. But that goes all over the body and has all sorts of off-target effects. It’s much, nicer if you can just do it topically. But it’s also more of a hassle.

Saloni Dattani: Yep. Then there’s omalizumab that I mentioned at the start. That was originally developed as an asthma drug. But more recently, it’s shown to be effective for various food allergies. Peanut, milk, yeah, various food allergies. Then you brought up Viagra, Sildenafil.

Jacob Trefethen: I didn’t bring that up! You brought that up!

Saloni Dattani: Sorry. You answered that to my first question.

Jacob Trefethen: Now, Viagra, I do expect, if I had to make a prediction, we will get another usage of Viagra. People actually talk about Viagra in the context of Alzheimer’s too. There’s not, to my knowledge, been a big trial of it.

Saloni Dattani: Interesting. That seems like something, we probably have enough people taking it now that we could find out.

Jacob Trefethen: That’s a good point. Look back at that data.

Saloni Dattani: Then there’s, yeah, a lot of antidepressants are also used for other conditions like anxiety. Then sometimes there’s a kind of related phenomenon where something is tested for one thing and then it turns out to be useful for something else.

If you’ve heard of KarXT or xanomeline-trospium, that is a new schizophrenia drug that was approved, I think maybe one or two years ago. It was originally tested as a dementia drug, but in those trials, I think in the 1990s, they found that it reduced hallucinations in those patients and then thought, oh, maybe we could use this as a schizophrenia drug. But the problem was that the drug had multiple effects. One was in the brain reducing hallucinations, but the other was that it caused really severe nausea and vomiting, and that’s because it also attached to receptors in the gut. So I think researchers tweaked it and added trospium to it, which prevents it from binding to those other receptors in the gut; it’s basically tweaked to become more specific so it only reaches the brain.

Jacob Trefethen: Which is a good sort of lens to apply here as well, where repurposing is not always you have one drug used for three diseases. Sometimes you get insight from the development of a drug for one disease that leads you to keep going and keep tweaking for a different disease. From a drug developer’s point of view, maybe the more common exciting story, I’m not actually sure, but that certainly is a common thing that is a bit different. You still got to do some chemistry after you get the initial.

Saloni Dattani: Right. You might tweak, you might change the way that it’s given so that it has more effects in one organ than another, or you might attach something else to it so that it can’t get into certain places that cause side effects.

Jacob Trefethen: From the point of view of a philanthropic funder, this is often something that sounds like a detail that can be quite important because there’s the magical hope is that you could fund a trial for a drug that already exists against a new indication and then it works. Then you don’t have to go through all of the original testing again, because you already have these big safety data from the first usage! That is really amazing from a point of view of health benefit without having to spend as much money. And that can happen.

The issue is often you’re finding these insights that you actually then do want to go back a little bit to the drawing board and make some edits to the chemistry. Once you do that, you then have to sort of re-enter as if you’re a new drug to some degree. So that can get you back into more traditional pharma land and that can cost a lot more money.

Saloni Dattani: Right. I guess what’s also interesting is that we’ve talked about a bunch of different types of drugs that have these multiple effects. Small molecule drugs, which are so small and they can get everywhere, they often have effects in different places. But also some peptides, like GLP-1s, have multiple effects, and also some antibodies have unexpected effects as well. I recently saw this study a few months ago where they tested all the approved antibody drugs and found that about a third of them had an off-target effect as well. Then there are gene therapies, which I guess that’s less likely because those are so focused on a specific gene.

Jacob Trefethen: But genes do multiple things sometimes.

Saloni Dattani: That’s true. That’s true. We’ve talked about ones where there is pretty good evidence so far that they can be used for different conditions. But what about some speculative possibilities about drugs that are used today that could be used for other conditions, and we don’t really know yet? Do you have any that come to mind?

Jacob Trefethen: Yeah. Oh, well, I hate to hop on one theme of Alzheimer’s, but the shingles vaccine and Alzheimer’s.

Saloni Dattani: That is one. I’m pretty skeptical of that..

Jacob Trefethen: You’re skeptical?

Saloni Dattani: But why don’t you make your case first?

Jacob Trefethen: Okay, I’ll make my case. There have now been four, I believe, independent, quite interesting natural experiments or observational studies that point in the same direction, that show that when the shingles vaccine got rolled out to different people who are older to prevent shingles. It looks like it may have also prevented the probability you progress into develop Alzheimer’s or dementia.

The first or the most sort of striking study of these four as far as I’ve seen is in Wales, there was a introduction of the shingles vaccine, where if you were born in 1933, I believe, the cutoff date was September 2nd, if I remember. If you were born before that, you were not eligible. If you were born after that, you were eligible. You have this really clean cutoff date where you can then see what happened to the people on either side of that, what an economist would call a regression discontinuity. The answer is that in that population, the people who did get the shingles vaccine were, after seven years, had a drop in relative risk of Alzheimer’s or dementia of 20%.

That is not as high quality evidence as a randomized controlled trial, which is what you would usually do for developing a new drug that went through clinical trials. However, it’s pretty suggestive. It’s- I’ve had friends who skeptical friends trying to poke holes in it, and I’ve heard different holes trying to be poked, but you usually have a rejoinder. It’s the kind of observation I’ve been saying, like, oh, maybe there’s something here. Then the fact that this has popped up in other countries as well, in other studies, is pretty interesting.

Now, the thing that I think is not known yet, so there hasn’t been a randomized controlled trial testing this yet, and there’s various questions that are one level detailed down, but that are very important. Question number one, in the trial, in the observational setting I just mentioned in Wales, the vaccine in question was the live attenuated herpes zoster vaccine. Now, there’s another vaccine that is now used in the US, for example, called Shingrix, which is the trade name, which is a subunit vaccine with an adjuvant made by GSK.

Saloni Dattani: Right. So both of these are shingles vaccines, and the studies that showed this benefit were using the old one.

Jacob Trefethen: That’s right. Well, one of them was. There’s that one that also trying to look at, well, hold on a second, with the modern shingles vaccine that was designed to be better for preventing shingles, is it also better for preventing Alzheimer’s? Is it the same? Is there any difference?

I’ve actually heard different opinions from different scientists on that. The evidence is not strong enough to give a good answer on that. Some people actually think it is, it’s going to be worse than the original live attenuated vaccine. Because of the way your immune system responds to live attenuated vaccines differently than sub-unit vaccines. Some people think it will be better. That’s a question.

Then another question is, okay, well, what’s actually going on here? Is it about shingles? Like reducing the amount you get shingles is the channel that reduces the amount you get Alzheimer’s. It’s probably not. There’s probably something else going on about, just at that age, jacking up your immune system to clear out a bunch of stuff. That is-

Saloni Dattani: So it’s not, you’re saying it’s not shingles necessarily that’s contributing to dementia.

Jacob Trefethen: Not necessarily. People are debating this now. They’re trying to chase down what is the mechanism of if there is a real effect here, why is there a real effect here? Could you get that effect from simply an adjuvant that boosts your immune system rather than a specific vaccine.

Saloni Dattani: I guess I want to get the shingles vaccine, but if I could just prevent it with just an adjuvant, then that’s really easy.

Jacob Trefethen: If I recall from a previous episode, you have trauma related to the chickenpox vaccine.

Saloni Dattani: Oh, that’s true.

Jacob Trefethen: You weren’t allowed to get it.

Saloni Dattani: It really depresses me that in most, I think in every country or maybe most countries, you can’t get a shingles vaccine unless you’re above a certain age, and that age is like 50 or 65 or something, even though lots of people younger than that get shingles.

Jacob Trefethen: Yeah. Some countries recommend it 65 plus. The US is now recommended at 50 plus. Imagine if there is a preventive effect against Alzheimer’s and we’re just YOLO-ing it, and it’s like, what the hell? Yes, that is a fascination of mine, and I am still reading up on it. But why are you skeptical?

Saloni Dattani: Why am I skeptical? I think, so there are multiple reasons that I’m skeptical. One is that, okay, it seems like there are many vaccines that are links to a lower risk of dementia. Not just shingles, but flu and DTP and various others as well. I have to say, when I see something, when I see results like that, I’m like, what if they’re all just confounded? What if it’s healthier people tend to get these vaccines and they have a lower chance of developing dementia? That doesn’t really apply to the study that you mentioned, of course.

But I have other reasons for skepticism there. One is the specific way that these studies were done is, as you mentioned, they’re looking at a particular birth date where, after that birth date, people were offered the vaccine and people before that birth date weren’t. Even though these are somewhat large studies, when you’re doing that comparison, the thing that matters most is how much that drop is just before and after that cutoff. The number of people who are just above or below that birth date in that year, it’s not that big. So the results that I’ve seen, they seem to be kind of marginally significant. I am sort of skeptical that they’ll hold up in larger samples. I think there’s an ongoing study with a larger population of the whole of England, instead of Wales, where they didn’t find any discontinuity. So I’m thinking there’s probably something going on there.

But I think that just in general, when you look at these kind of cutoff studies, you often have to ask, what if something else changed there as well at that same time? That it was not just getting eligible for that vaccine, but also maybe that was the start of the school year and maybe grandparents with little grandchildren have a higher risk of getting shingles or something, I don’t know, whatever, something like that. There’s like little nigglings in my mind that make me think, I don’t know if this will hold up. I would say I’m pretty unconfident that it will hold up, but I would say probably about 20 to 25% chance where I think maybe it will actually prove to be true and that seems high enough to warrant more attention. But I’m pretty skeptical.

Jacob Trefethen: I would take the bet against that. I think it’s higher chance than that. I’m curious how you think about the evidence from other countries. You mentioned the England evidence that’s kind of ongoing. I should know more than I do about it. But what about the Australians? What about all these other countries?

Saloni Dattani: As far as I’ve seen, they’ve also been just marginally significant. When I look at that, it’s a bit... When you tweak certain things in your statistical analysis, you can get things that are marginally significant. There’s a really cool blogpost by a friend of mine on the Uncanny mountain of P-values. Basically, if the literature is full of results that are barely statistically significant, or just under the threshold, that’s a warning sign that the effects might not hold up.

Jacob Trefethen: Do you think that there is a real effect, but it’s so small that it won’t be detected? Or you think there’s not even a real effect?

Saloni Dattani: I guess this depends on, how small of an effect can we detect? My guess is that it’ll be too small to matter.

Jacob Trefethen: Got it. Okay.

Saloni Dattani: But I hope that I’m wrong. Anyway, shingles vaccines are just good. Shingles is terrible. It’s painful. Take it anyway!

Jacob Trefethen: Okay, so let’s just step backwards and could there be more drug repurposing than there is? Is this a panacea, Saloni? What do you think?

Saloni Dattani: What do I think? I do think with many of the examples that we’ve talked about, we only found out that they could be used for something else pretty late. With aspirin, for example, that’s been used for over a century, but people only really established that it could be used for cardiovascular disease in the 1980s. Then there’s dexamethasone during COVID - that was originally a steroid, and it took public funding to run a trial to find out that it was useful for COVID as well. There’s another one I read about recently called moxidectin.

Jacob Trefethen: Yes, moxidectin, yeah.

Saloni Dattani: Right, which was originally developed as a, I think, deworming drug for animals, is that right? It was a veterinary drug in the 1980s. People thought, oh, maybe we should try this out for worm infections in humans as well. But there was just not really a market for that because people who are most affected by that live in poverty, they’re children in poverty in Africa and south Asia, for example. So there wasn’t really interest in funding the trials for it and actually proving out that it works and getting it to market, until a nonprofit did that in the 2010s and more recently. Their trial showed that it could cure 70% of whipworm infections in kids in Tanzania.

My view is, okay, there are a bunch of examples where it took really long to figure out that these drugs that were already there were gonna be effective for something else. That suggests to me that there must be other drugs right now that are gonna take a long time to be found effective for something else. So that’s my optimist take on that.

Jacob Trefethen: Okay, let me be pessimistic then. If a drug had a really useful use, you usually spot it because people taking it will experience that side effect. Everything else is minor in comparison.

Saloni Dattani: What if they don’t have the other disease though? What if they’re like quite different things and there isn’t that much overlap?

Jacob Trefethen: Hmm... You got me. The more public health benefit you want, the more it has to be a common disease. But you are, it is true, unfortunate. Wow, I didn’t manage to stay skeptical for very long, did I? It’s true that you can often, there are many diseases out there and you won’t have collected evidence for the utility against most. That’s true.

Saloni Dattani: I guess one reason that, when I first heard about this topic, I was pretty skeptical and I was like, isn’t pharma already doing this? Aren’t they already testing for whether their drugs work for multiple conditions? Because if they did, then, you know, that’s a larger market. That’s more money. Why wouldn’t this be happening?

I also, I know that pharma companies individually have hundreds of thousands of compounds in their libraries and often they will just mass screen all of them against the diseases that they’re interested in. And so, aren’t they just doing this already? How can there be more that we haven’t found?

Jacob Trefethen: What I would say to that is that presupposes we understand these diseases and we usually don’t. You can’t actually do a screen that tells you the truth because diseases are very complex and manifest in ways that are not just about cellular receptors, you know. Often you discover these things that you wouldn’t expect just in virtue of complexity of the body. So that one, yeah, I think screening can’t be the whole story.

Saloni Dattani: It also sort of made me think that often when pharma companies are testing these hundreds or thousands of drugs, they often start with a disease, or they start with a target, and they’re like, which of the many drugs we have work against that target? I think it’s less common that they have all the drug compounds and they’re like, which of the hundreds of different diseases do these work against? Because that’s like way too many combinations as well.

Jacob Trefethen: Yes, the combinatorics. Then, in addition, the amount of money that you can make off of different drugs for different diseases varies by orders of magnitude. If you’re a company that’s trying to make sure it doesn’t go bust, then you won’t be putting the same amount of energy behind leprosy as you would be behind cardiovascular disease.

Saloni Dattani: One other reason that I am a little bit skeptical, or was a little bit skeptical, was lots of attempts at repurposing drugs have failed. For example, metformin, there was a lot of hype around that.

Jacob Trefethen: There’s still hope on that!

Saloni Dattani: Oh there is? There was a lot of hope that it would be a cancer drug as well. There were a lot of academic trials on this. The same is true for, I think, vitamin D in various different conditions as a treatment. Most of, I think so far, the conclusion is that they don’t work for those.

But one of the interesting things about that was that the evidence for this before the trials were done were observational studies. Some of these observational studies were affected by various biases. One of these biases is called immortal time bias. Have you heard of that?

Jacob Trefethen: I’m pretty biased myself as a immortal demigod. Yes. But what about you?

Saloni Dattani: I had, well, I had heard about this for a long time and I was like, what does that, why is it called that? I feel like hardly anyone had given me an explanation of this that made sense. It was like really complicated and people would explain it with these diagrams that were very difficult to read.

But the basic idea is that you have, you’re looking at like, let’s say hospital data or something, and you’re comparing people who have taken a drug to people who haven’t. You look at, while they’re on the drug, what are their chances of developing the disease versus people who are not on the drug?

What a lot of these studies would often do is that they count the time that people are not on the drug, or before they start the drug, in the control group, and they take the time that they spend on the drug in the treated group. But that creates a problem. You’ve like already lived up to a certain age before you get to the treatment group, which means you’ve sort of lived longer by definition. The only way that you could be prescribed that is if you’ve lived a certain amount of time.

This affected a lot of the studies that were claiming there were benefits of metformin for cancer. That is called immortal time bias, because when you start getting on the treatment group, it’s like you’ve been immortal until that point, and that’s the only reason you’ve been included in the study. You can’t have died.

Jacob Trefethen: Right, right. Yeah, that’s a sneaky one.

Saloni Dattani: There’s also another bias that’s often called confounding by selection, which is that the people who get prescribed a certain drug are different in some systematic way from the people who don’t. So in a randomized trial, you’re randomly deciding to put some people on the placebo versus some people on the treatment. But that’s not true in the real world. People who get certain drugs might have a more advanced stage of the disease. Or with vaccines, often it’s healthier, more educated people who will get vaccines as adults. Or for certain vaccines, like the rabies vaccine, it’s often people in certain occupations, like they’re vets or something else, that get the vaccine. They’re systematically different, which might mean that they’re healthier in some way.

Jacob Trefethen: Anything observational is more stressful. It is true. I have to admit that.

Saloni Dattani: Yeah. Yeah. I think there’s just, there’s a lot of uncertainty and many or maybe most repurposing efforts will fail. I think this is why randomized controlled trials are so helpful. But I wouldn’t lose faith in the whole idea. Most clinical trials also fail, but some of them work. You shouldn’t assume that because many or most of them will fail that they’re not worth trying.

Jacob Trefethen: Let me give another pitch that there might be a goldmine out there and see what you think. One issue from a pharma company’s point of view on repurposed drugs is that if a drug has been approved for one use, then it’s sort of like an immortal time bias for drug patent length. It’s quite likely the patent has expired by the time you have suggestive evidence for second use. If I’m a company, why would I pony up $75 million to confirm an effect that then anyone legally can sell that drug? Because I don’t have a patent anymore. So what do you say to that? Doesn’t that imply there’s all of this low hanging fruit because companies aren’t paying for these trials? Why would they? We got to pay for them as taxpayers!

Saloni Dattani: I think you’re right. I think, well, the counter argument to this is that a lot of the companies still do trials before the patent expires. So maybe they’ve- if they’re taking so long to start running a trial, maybe that’s because there weren’t these other uses at all.

Jacob Trefethen: It takes a while to accumulate off-label data. I don’t know. I think, the aspirin case, it was literally decades and decades, right? I don’t know.

Saloni Dattani: No, you’re right.

Jacob Trefethen: Now, what I will say is I just have to give a shout out to one of the best trials of all time. Any guess what I’m about to... which trial that is?

Saloni Dattani: I don’t know. What are you thinking of?

Jacob Trefethen: What do you mean you don’t know, Saloni.

Saloni Dattani: RECOVERY?

Jacob Trefethen: Yes! RECOVERY! Yes! Okay, so let’s say you find yourself in 2020, which I do not recommend.

Saloni Dattani: For many reasons.

Jacob Trefethen: For many reasons. There’s an issue you face, which is an incoming global pandemic. If you want to develop a drug against COVID from scratch, it’s going to take a while because it just came out of nowhere. It’s a great time to see whether there’s a repurposed drug that could work. However, most of these drugs are off patent, because they have been around for decades. Time is of the essence. So what do you do? If you are Martin Landray and collaborators and Peter Horby, I believe, at the University of Oxford, and if you are the UKRI and MRC, the two funding agencies in the UK government, and then later, if you’re the Wellcome Trust and the Flu Lab, what you can do is fund a trial that has many arms.

You have people who are like, ‘Hydroxychloroquine is gonna prevent COVID!’ Great, chuck it in the arm. We’re gonna test. We’re gonna have some people on a control group. Okay. ‘What about, dexamethasone?’ ‘No, that’s very dangerous. You don’t want to be giving people a steroid.’ Let’s try it out. Chuck it in the arm. They had all these different arms. Then by June, 2020, which is months before vaccines, they had managed to find that hydroxychloroquine didn’t work. Some other things didn’t work. Dexamethasone did work.

And then within the day, they had, well, they had to confirm that it wasn’t spurious. They like really double checked the data before that press release went out. Then they, within the day, the NHS system in the UK absolutely flipped and said, okay, if anyone comes in, gets hospitalized with COVID. Now we know what we can give them, it’s going to reduce their chance of death. It’s a stunning result. People have tried to model out how many lives that saved. The most prominent modeling, which I haven’t gone deep to vet myself, but suggests that within 12 months that saved a million lives around the world. Oh my goodness. Just unbelievable. You could not have known ahead of time. People were saying all these different stuff. People were making all these different predictions. And they got the data. Oh my gosh.

Saloni Dattani: People have so many hypotheses and it’s hard to know which ones are actually going to work. There are probably some good reasons to believe all of them might have worked. It’s so useful to actually run the trials and figure out which ones they are. The wonder of repurposing. Save millions of lives.

Jacob Trefethen: Completely. I think that when you look at, okay, how can we repeat that for different areas? My suspicion is that you’re just not going to have many areas where you’re getting a 90% reduction from a repurposed drug. Then maybe you will have some areas where you’re getting a 20, 30% reduction. Okay, you’ve got to be kind of looking for these population-wide things. That sort of changes the catchment area a little bit. It makes you want to go cardiovascular. It makes you want to go maybe Alzheimer’s. But I’m not so sure it will be. Yeah, I guess I hold out less hope for 90% reductions.

Saloni Dattani: I think that brings me to another reason for optimism, which is that some diseases just don’t have a large enough commercial market that companies would even be willing to try to test them for them. Like they’re not interested in repurposing something for a tropical disease where there isn’t that much money in developing those drugs anyway, or diseases like addiction or something like that, where people who have them aren’t able to pay for them. That makes me think there are a bunch of diseases like this where we don’t really have the incentives for pharma companies to test them, even if they are on patent.

Jacob Trefethen: Yup.

Saloni Dattani: I think the other one, we mentioned a few vaccines, but I think this also applies to vaccines especially because once they’re universally recommended and you test them out for a different thing, you’re not going to get a larger market from doing that. You’ve already put it on the market. It’s already recommended to everyone. You’re not really going to get much more of a benefit from doing that.

Jacob Trefethen: I disagree on that one. I think GSK has a massive incentive to test Shingrix against Alzheimer’s because the Shingrix vaccine, it’s not exactly your top priority for everyone. Something like a third of people who are eligible actually get it. It’s a painful vaccine, massive adjuvant jab. A lot of people don’t go back for their second dose. If it were known that you could reduce your chance of Alzheimer’s by 20%, I think that would go to, they probably double their sales, so that’s, I think they have a big incentive personally.

Saloni Dattani: I guess, yeah, I agree with that, but I think vaccines tend to have a lower price than other drugs, and so that would make it hard for them to- and I don’t think that they would be able to raise the price that much.

Jacob Trefethen: Yeah, interesting, yeah.

Saloni Dattani: I think the last reason is that I think, even though there is this economic incentive to testing drugs for new conditions, that incentive is going to kind of run out once the patent expires and generics enter. Because like you said, if you’ve tested it for some new condition, you’ve like spent the millions or tens of millions of dollars on these clinical trials, and it turns out, okay, it’s useful for something else, well people can just get the generic version anyway, and they’re much cheaper. What’s the point of doing that?

Jacob Trefethen: Yeah.

Saloni Dattani: There’s a really interesting paper that basically looks at drugs that spend longer in clinical trials and therefore, when they finally get to market, they have a shorter patent life remaining. Those drugs tend to be repurposed less. That suggests that there are economic incentives that can run out. If you look at the kind of repurposing efforts over time, after the patent is issued or after the drug is approved for the first thing, it kind of slowly declines over time. Companies are trying, once the drug is approved, to test it out for lots of different things. Then when it reaches the end of the patent period, they’re like, ah, well, the generics are just going to undercut us.

But there is this, there’s a little bit of like a back and forth here because I think that, often when people hear about this, they’re like, well, don’t pharma companies do all these sneaky things to lengthen their patent lengths anyway? Can’t they just get around this by doing that instead? I think that’s sort of true, but there’s a limit to how true that is.

Jacob Trefethen: Only so much you can, you can finagle.

Saloni Dattani: Have you heard of some of these sneaky tactics?

Jacob Trefethen: Let me invent some. Here’s what I would do. Okay.

Saloni Dattani: What, you’re the pharma company?

Jacob Trefethen: Yes. I would, if I think, oh, hold on a second, there might be a off-target effect here that’s beneficial instead of harmful. Okay, here’s what we do. We go back and change the molecule by the minimal amount to generate a new molecule according to the US Patent Office. We generate new data on that molecule and we submit a new patent. We say, we just invented a new drug. Then we want it to have not changed that much, because the effect might disappear. Do people do that?

Saloni Dattani: That’s true. People do that, but can’t the generics just use the original version and say, hey, well.

Jacob Trefethen: Damn, wow. I’m so stupid. I’m such a bad- That was crazy. I completely missed that. Okay, let me think. Yeah, you have to then actually, well, that’s pretty cool. The system’s aligned with benefit pretty nicely because you have to then make it a better drug.

Saloni Dattani: Yeah, right.

Jacob Trefethen: I guess, yeah. Okay, here’s my new scheme. I make it so that it is demonstrably slightly better. Then the way that drugs work, you get a winner-takes-all effect where no one wants a slightly worse drug, you know? Everyone wants something that’s slightly better. That takes 100% of market share regardless of price. How does that, how’s that?

Saloni Dattani: Is that true? I feel like if I, if the brand name drug was like 5% more effective, but the generic drug is... 10 times cheaper or whatever.

Jacob Trefethen: But consumers don’t pay. The health system pays. You might get negotiated by the NHS on that. You won’t get negotiated in the US though. I’m exaggerating. In some cases, you will.

Saloni Dattani: I was going to say that there’s this thing that generic companies can do. Let me sort of take a step back and explain how this works. Let’s say I’m the brand name drug company and I have developed drug for this thing, this one condition, diabetes, and then I’ve also tested it for weight loss. I would put both of those things on the label, but the diabetes thing came first.

A generic company, let’s say that’s you, you could decide, I’m just going to say that this is used for diabetes on the label and not also for weight loss. But doctors know that it’s the same molecule and it can be used for weight loss as well. So they can just prescribe the generic drug for weight loss.

Jacob Trefethen: But your point being that patent protection, it doesn’t really follow an indication, it follows a molecule.

Saloni Dattani: It follows an indication, but... you have to, the brand, the company that has the brand name drug has to prove that the generic company actively is trying to prescribe, get it prescribed for that second use and that’s quite hard to prove. You get undercut by the generic company.

Jacob Trefethen: Right. You’re not going to confirm that effect necessarily with a trial.

Saloni Dattani: Yeah. The patent extension or whatever is only helpful if the generics haven’t got in.

Jacob Trefethen: Got it, yes.

Saloni Dattani: There’s another thing you can do as the original brand name company, which is that you can switch patients to a different version of the drug. You can say, oh, you know what, instead of this twice-daily drug, you should take the once-daily drug instead, or once-daily version instead. If you do that, then those people can’t get the generic drug instead of your brand name drug, if they’re prescribed it. At pharmacies, they can automatically prescribe you a generic drug if it’s the same dosage and stuff, but they can’t if it’s slightly different.

Jacob Trefethen: That’s really interesting, yeah. That makes sense.

Saloni Dattani: Okay, so there are all these things, there are all these economic incentives that can affect whether generic repurposing happens. My conclusion is that there are probably a lot of repurposing efforts that aren’t happening.

That’s probably especially true for drugs that are already off-patent and that are generics. It’s probably true for things where people can already get these things very cheaply and they’ve existed for a long time, like vitamins and supplements.

Also for diseases like tropical diseases or diseases of poverty where the market and the incentive for a pharma company to run these clinical trials to try to do repurposing isn’t really there. And also for diseases where the clinical trials take a really long time, because if they take a long time, then you have a shorter time still on patent and you have less time to recoup that investment.

Finally, I think it’s probably also not happening as much as it could for vaccines. My guess is that the reason for that is that companies are trying to, generally when you’re developing vaccines and they’re used universally by children, by like 80 or 90% of children, and they’re healthy children otherwise, you kind of want to limit how many off-target effects, how many side effects there are. So you’re trying to make them as specific and precise as you can, and because of that, you’re just looking for toxicity.

Jacob Trefethen: Right. I would add in the optimism column from this episode for me is it’s just so nice that for repurposed drugs, you have an existing large safety dataset. The existing safety data is just such a boon. If you can find these now, I will give my pessimistic take from this episode is that I don’t think you’ll get many miracle drugs in the sense of I don’t think you’ll have these massive cures and reductions. I think you’re going to be improving various markers similar to the weight loss drugs by meaningful amounts, maybe you’ll be reducing your risk of heart attacks by 10 or 20% with something or reducing your risk of Alzheimer’s if we get a repurposed drug for Alzheimer’s. But I don’t think we’ll get an Alzheimer’s cure this way.

Saloni Dattani: Aww.

Jacob Trefethen: Sorry. You don’t even think the shingles vaccine works!

Saloni Dattani: Well, I don’t think the shingles vaccine works for dementia.

Jacob Trefethen: We have to come back in five years and see who is right about that.

Saloni Dattani: We definitely should.

Jacob Trefethen: Okay, so we’ve learned about repurposing drugs and I wanted to check with you right now. If I, instead of injecting Mounjaro in my thigh, injected it somewhere else, would different effects happen? If I injected it in my scalp, would it be a baldness drug? What do you think?

Saloni Dattani: Wow. This is hard. I know that-

Jacob Trefethen: I don’t think it’s hard.

Saloni Dattani: You’re trying to lose weight somewhere else?

Jacob Trefethen: No, no, no, no. I’m trying to have a different effect that I want. But because it’s a magical drug, you can have any effect depending where you inject it.

Saloni Dattani: Ooh. Hmm. You know what I would like?

Jacob Trefethen: What?

Saloni Dattani: More hands.

Jacob Trefethen: You want an increase of 50% in hands?

Saloni Dattani: Yeah. You could do so many more things with them. You know what that would make really easy? Juggling!

Jacob Trefethen: How frequently do you find yourself juggling?

Saloni Dattani: Never. I’m so bad at it.

Jacob Trefethen: You don’t have more hands.

Saloni Dattani: Exactly. It’s because I don’t have more hands.

Jacob Trefethen: Also there’s complementarities, because if you had more hands, you could inject more Mounjaro quicker. You could get the benefits of other drugs too.

Saloni Dattani: This is what I’m missing out on. What about you? What’s your answer?

Jacob Trefethen: If you had more hands, would you also want more feet?

Saloni Dattani: No. What do you do with feet? You just walk and run. They’re not that useful. You’re not picking up stuff with them.

Jacob Trefethen: I think if you had four feet... Now I’m just thinking, would I have four legs?

Saloni Dattani: I’d be a centaur.

Jacob Trefethen: Maybe if I had... Here’s what I want. Instead of two flat feet, lame, pathetic, I want two curved, kind of like...

Saloni Dattani: Oh, wow. Like a rocking...

Jacob Trefethen: Yeah, yeah. Exactly. Then walking would be kind of fun. I actually got taught how to walk once. You’re meant to land on the...

Saloni Dattani: You didn’t know- sorry, you got taught how to walk? What is the context of this?

Jacob Trefethen: Like in the sense of by a gay person, like how do you, how do you walk in a way that’s like chic?

Saloni Dattani: What?

Jacob Trefethen: You, I can’t even remember now. Wait, let me just practice. You go, yeah, yeah. You have to, you have to do the weight right at the heel and the ball of the foot, but I can’t do it without doing it live. I can’t explain it. You wouldn’t get it!

Saloni Dattani: Okay... sorry.

Jacob Trefethen: Anyway, point being, it’s a bit like a rocking horse. I think you could walk better if you had a rocking horse.

Saloni Dattani: This is a very strange choice of off-target side effect you want.

Jacob Trefethen: Okay, fine, fine, fine.

Saloni Dattani: You want to turn into a rocking horse.

Jacob Trefethen: Let’s see, what else do I want? Maybe it would be nice if... If you had the thing that would just give you massive muscles, would you do it? I guess we do have that. It’s called a steroid.

Saloni Dattani: I think, yes. Well, not massive, but bigger. No, I don’t take steroids.

Jacob Trefethen: I just entrapped you. I’m actually a police person.

Saloni Dattani: Oh, no. The other thing that made me think of was, I would love to be taller than I am. I’m very small.

Jacob Trefethen: They have that too, growth hormone.

Saloni Dattani: It’s too late for me to take that, isn’t it? I think it’s when you’re growing up.

Jacob Trefethen: It’s true. It’s true.

Saloni Dattani: I used to stretch more. When I was a teenager, I was like, maybe if I stretch more, I’ll get taller.

Jacob Trefethen: That’s so depressing. You were like, do they still have any of the torture racks that they used?

Saloni Dattani: Not that extreme. I don’t know. I just thought it was, I was like, maybe this is one of those things that’s like a ‘use it or lose it’ situation. The more you stretch, the more your body is like, oh, she needs to be taller than she is.

Jacob Trefethen: It can sense. Yeah. I guess I’m trying to think, would I want a tail? I don’t know if I need a tail.

Saloni Dattani: What about a tail that can drop off and regenerate itself?

Jacob Trefethen: Definitely better than a tail. Why not have the optionality, if you’re going to have a tail? Yeah. I think if I had a tail, I’d want it to be really long.

Saloni Dattani: To do what with?

Jacob Trefethen: Just to curl around my legs.

Saloni Dattani: Like Rapunzel.

Jacob Trefethen: You know how Italian people will gesture with their hands? I want to gesture with my tail.

Saloni Dattani: I was thinking of Rapunzel. You could let down your tail and someone could climb up.

Jacob Trefethen: I live on a first floor.

Saloni Dattani: Yeah, that’s not very useful.

Jacob Trefethen: People are always trying to climb in. Anyway.

Saloni Dattani: She uses her hair for martial arts and stuff.

Jacob Trefethen: Which presumably hurts.

Saloni Dattani: As a weapon. Yeah.

Saloni Dattani: So I guess our conclusion is there are probably a lot of repurposing efforts that aren’t happening for various reasons. According to economists, the value of that or the missing amount of innovation that’s not happening is pretty large. The estimate is around 100 to 400 billion dollars per year in social value that’s not happening because of all of these misaligned incentives. So this seems like a really important problem to solve. What’s helpful, as you mentioned, is that these are drugs that are already approved for something, so we already have lots of data on them and it wouldn’t be that hard to test them out for new conditions as well.

Jacob Trefethen: With that in mind, what are some of the- not the scientific things that can help with drug development, but some of the economic or regulatory or, related to patents policy? What are some things that we could do that would improve the system here?

Saloni Dattani: I think there’s probably a lot of things that we could do. I guess the basic idea maybe that I should re-describe is that in general, when pharma companies do more repurposing, or they’re testing their drugs for more conditions, they have a larger population of patients that the drug can be prescribed for, so there’s a larger market. There is an economic incentive to some degree to test drugs for new conditions. But that incentive is kind of time limited because once the drug goes off patent, and generics can enter the market, they can get outcompeted by those generic manufacturers and it becomes no longer worth it to run trials and expand the uses.

I think this is more of a problem for small molecule drugs, because it’s really easy for generics to develop their own version of the small molecule drug in general. It’s easier to develop small molecule drugs and cheaper, and they can get into the market pretty quickly. It’s harder for biological drugs like antibodies and vaccines. That’s for two reasons. One is that those drugs tend to have twelve years of exclusivity once the drug gets approved, rather than five. But also it’s just harder to develop those, you need a lot of technical know-how, it’s more expensive for generic manufacturers to develop them.

Based on that, how do we get more repurposing, more of the ideas? I guess the obvious one, which is probably, which I think is often pretty unpopular, is just extending the length of the patents. But right now, you don’t extend your patent length for a new use. You get more exclusivity on the market. It’s slightly different. The U.S. Patent Office gives you a standard length of 20 years after you file for a patent. A company develops a drug, maybe immediately after they develop it, they file a patent for it, they get the patent. For 20 years, they have the exclusive rights on producing that thing.

Then once it gets approved at any point during that 20 years, the FDA then gives them an additional five years where they’re the only people that can sell the drug for that condition. The idea would be either you could extend the length of the patent so it’s more than 20 years, or you could extend the exclusivity period that the FDA gives you after the first use is approved.

If you get another use approved, then you get another three years of exclusivity for that new use. But that’s only helpful if it’s before generics become available on the market. I think the downside is higher prices for longer, but the upside is there’s more of an incentive to test new uses for these drugs at all. And we find out about new uses of drugs that we wouldn’t have known about before. Does that make sense?

Jacob Trefethen: Yeah, maybe. This stuff is complicated though because you have more of an incentive for one company, that’s true, but you do incur more deadweight loss because you have a monopoly for a longer period. Yeah, I’m not sure I have a clean intuition that will point me in the right direction. My intuition could take me in either one.

Saloni Dattani: Can I give you a weird example? It’s actually, it’s not the same. It’s not what we’re talking about, but it’s kind of related.

Colchicine, the gout medicine, it’s an ancient gout remedy. I think it was probably properly developed as a medicine in the 19th century for treating gout. For drugs that are developed so long ago, before the FDA even existed, before drug regulation existed, and that were already on the market, they weren’t approved and the generics weren’t approved either. They just were there already- they’re sort of approved to be used because of that ancientness.

At some point, I think the FDA developed this pathway where they wanted to get companies to test whether these drugs were actually effective, and if they were effective for different uses as well. What they said was that, if you do test these existing grandfathered-in drugs for some other condition, then you will get exclusivity to sell them. There was this company called URL Pharma, which tested colchicine, I think for gout or maybe it was for cardiovascular disease. They found that it was effective. The trial succeeded. The FDA was like, okay, cool, now you get exclusivity. They actually cleared out and like shut down all of the unapproved competitors. This became the only one on the market and they raised the price massively and everyone got really mad. Understandably.

Jacob Trefethen: Wow. Extending patent length. That’s maybe a pretty big one, kind of blunt. Are there other options?

Saloni Dattani: What do you think?

Jacob Trefethen: There’s the classic, you know, two approaches to the economy as supply and demand, Saloni.

Saloni Dattani: Oh, really? What?

Jacob Trefethen: Yeah. When you put that in funding terms, you sometimes get into push and pull, where push funding is-

Saloni Dattani: What I’m getting really confused with, with doors.

Jacob Trefethen: Yes, yes. Imagine a door that could go both ways, sort of like an operating theater. No, the push means sort of grant funding investment. There’s money coming from some financial entity into some operating entity to run trials or to do something or other. Then pull funding is on the demand side. You’re saying, okay, because you’re not going to get a big payout because of all this generic entry, we have some other way of paying out.

Saloni Dattani: It’s like, if you develop the thing, we’ll pay you.

Jacob Trefethen: Exactly.

Saloni Dattani: Whereas the push funding is like, we’ll pay you to try to develop it.

Jacob Trefethen: Exactly. Yeah. I would look at both sides of this. I would say, if there’s a market failure in the sense of there’s not a private incentive for companies to generate this knowledge about whether a drug works well, number one, you can make grants. To those companies, to other entities to generate the knowledge. That’s push funding.

Number two, you could create prizes or payoffs of some form out the other end, where you say, okay, it’s not that you’re going to be able to charge a ton for this drug because there’ll be generic entry, but whoever can generate the knowledge gets a big payout. Here’s a hundred million dollar prize! Those are the two things that come to mind. What do you think?

Saloni Dattani: I really like those ideas. I think that maybe they’re useful in different situations. With a prize, you’re giving a prize for someone who can successfully test that a drug succeeds. Why would you do that? Why not just pay the company, or why don’t you just run the trial yourself? I think often the prize is more helpful when you’re not sure what the succeeding drug or vaccine or whatever will be.

You’re like, you guys try it out and you guys fund the trials. If you made the right bets, you’ll succeed and you’ll get this prize at the end. I think maybe what’s difficult about a prize is actually deciding how much the prize should be. Like, what if it is really obvious and you just didn’t know that and you might as well have just funded the trial?

Jacob Trefethen: That said, one of the nice things is you only have to pay out if it’s successful, depending on how you design the prize.

Saloni Dattani: What if the prize is too small, though?

Jacob Trefethen: That’s true. Then you have dangled something that hasn’t had any effect, but it’s better than paying for a bad outcome, which happens all the time in grantmaking.

Saloni Dattani: That’s true. I guess with the prize, the other thing is that, especially if the thing is already a generic drug, you have a prize for showing that it works, and then immediately the generic drugs can be used for a very low price. I think the other side is, maybe you have examples of this where you were pretty confident that certain things might work so why not just fund those research groups themselves, instead of having a prize or something at the end?

Jacob Trefethen: Laying my cards on the table, my biases are often in that direction. That’s because I am a grant maker though in my day job where, people say, but how are you going to pick winners? What if you don’t know? I’m like, well, how bad do you think I am? Come on.

No, I basically think that people often, economists often have an instinct of: you don’t know anything, you have to let the market decide; if there isn’t a market that works, you have to create a market. That’s a healthy instinct in some cases.

Then people like me think they know things. I’m kind of like, well, yeah, but actually I’m pretty sure we should fund this one and this one and it might actually go pretty well. So yeah, there’s a healthy tension between the two.

I think you want to be looking, the cases where the pull funding and prizes appeal more to me are when you have some reason to think that there is knowledge and data that’s dispersed throughout different firms and the economy broadly, that you’re like, oh yeah, I definitely don’t know. In some cases, I can point to those better than others. I’m sure that there is internal data on how different drugs get used that I’ve never seen that will be useful for some companies making a decision about whether to go after this prize or not in some circumstances. So there, I’m not omniscient.

Saloni Dattani: That makes sense. I guess there’s also, even with the pull funding, you have to have some people to decide that it’s worth the investment and to do the push funding. You have the prize at the end, but you need the companies, or the researchers, to decide that they think that their own candidate has good enough chances that they’ll fund the trials to get to that finish line at all.

Jacob Trefethen: Indeed, which means that the prize has to be much larger than it costs to run a trial because there’s some probability they’ll fail.

Saloni Dattani: Have you heard of CASPR?

Jacob Trefethen: I have heard of CASPR. Do you mean the addiction thing?

Saloni Dattani: The ghost.

Jacob Trefethen: I hear him right now. Ah!

Saloni Dattani: They’re the Center for Addiction Science Policy and Research, CASPR, and they’ve proposed a program that is trying to help do repurposing for off-patent drugs and supplements. Their idea is that there should be a program that is led by the NIH that funds and runs many trials for off-patent drugs, peptides and supplements, to see whether they work for other conditions. That is an exact example of one of these push funding uses, where you’re paying directly for the trials. And also the RECOVERY trial was actually-

Jacob Trefethen: Exactly. The RECOVERY trial was some of the best push funding we’ve ever seen. Genuinely, if you run the numbers there, my goodness, that costs maybe $20 million. That’s over a million lives. That’s just shocking. But you don’t get many trials that are as urgent as that, in the sense of we have no treatment for this new thing.

Saloni Dattani: I think that one was also maybe cheaper than usual because it ran through the NHS, the UK’s public health system, where people were already in hospital for COVID and it was just an extra additional one or two page form that they had to sign to be participating in this trial. They’d randomly get assigned to one of the many drugs that was in the trial. It wasn’t very much of an additional cost. It wasn’t like running a separate trial in these different academic centers or hospitals. It was already people who were already getting treated for stuff.

Jacob Trefethen: Yep. Yeah. If you were, if you as a listener happened to be in the RECOVERY trial, you are a complete fucking legend. That is so epic. Thank you for doing that. That applies to all of our listeners who’ve been in trials. I know a bunch of you have. It’s so cool. It’s like, it’s a great, it’s just a wonderful thing to do for other people. I am glad that some of our listeners are so, kind as to give to the rest of humanity.

Saloni Dattani: Right. Have you, I think maybe in a previous episode, you also mentioned EveBio, which is kind of working on this as well, from a scientific perspective.

Jacob Trefethen: That is right. Full disclosure, I am such a fan of EveBio that at the OpenAI Foundation, we just gave them some money to do more stuff.

Saloni Dattani: Oh, cool.

Jacob Trefethen: But yeah, they’re amazing.

Saloni Dattani: Tell us, tell me more about them.

Jacob Trefethen: They’re a repurposing outfit in some sense, although we actually funded them to do something a little different. But they’re taking in their original mission of all FDA-approved molecules and running that against running them all against a set of receptors on cells and seeing what happens, and generating a dataset that they then just drop into the public domain as soon as it gets created. That can give you more insights into can you repurpose any of these drugs for some effect you might not have thought.

Saloni Dattani: I found this really interesting, but I also, I think when I heard about it, I was like, aren’t pharma companies doing this already? They have these huge drug libraries, aren’t they already testing them for other effects?

What I found out was that, that’s true to some degree, but I think what pharma companies are usually doing is trying to test their drug compounds against specific off-target receptors, or whatever, that are listed as being important for safety or toxicity. They’re not testing them against all- or more receptors than that. Also, as I mentioned before, they’re often, you start with a specific disease that you’re interested in and you’re testing the drug compounds to see how they affect the receptors involved in that disease. You’re not doing like a much larger thing where you’re testing lots of drug compounds against lots of targets or lots of diseases. Whereas this is trying to create that matrix.

Jacob Trefethen: It’s really cool. You might- there’s lots of additional things you can do, lots of edits you can make, but what a cool start. That group in particular just is so into open data. You can just go on their website and you can start clicking around.

Saloni Dattani: Ooh. I read something else about them, which is that they’re a time-limited single-mission non-profit. Is that right?

Jacob Trefethen: They’re a Focused Research Organization. Yeah, they were originally founded with the idea of let’s do this in five and a half years.

Saloni Dattani: Oh, wow. And then once that happens, they were planning to shut down, but maybe they aren’t anymore.

Jacob Trefethen: We’ll see. They’re so good that they might accidentally stick around. But yeah, we’ll see. I don’t know. You’ll have to ask Elaine, the CEO. She gets to decide.

Saloni Dattani: Oh, cool. Maybe they would just shut down that project and do something else. That’s very cool.

Okay, so let’s do a quick summary of the different ideas we talked about for trying to get more repurposing. The first one we mentioned was, extending the patent term. I think probably this is pretty effective, especially for drugs where there is a large commercial market for producing new drugs for that use, but it takes a long time to run clinical trials for it that eats away the patent. Probably just, well, it doesn’t work at all for drugs where the generic is already on the market because the generic can just undercut them immediately. It probably doesn’t work very well for tropical diseases or rare diseases or diseases of poverty and addiction and things like that, where customers are too poor to pay for them.

Jacob Trefethen: What about reimbursement for off-label uses?

Saloni Dattani: What is that?

Jacob Trefethen: What I’ve heard is certainly in a US context that a lot of what happens in terms of how you make revenue as a company, a drug company, is about reimbursement codes. Does that play a role here?

Saloni Dattani: It does, yes. So helping people track what off-label uses a drug is being prescribed for as well, that could help you collect more data, which might suggest to you that this drug could be effective for something else as well. Then you might then run the trials for it. But also it can result in different pricing depending on which diseases they’re prescribed for. That would give more of an incentive, I think, for companies to test these new uses.

Jacob Trefethen: We also talked about prizes and push funding with public or philanthropic funding. With prizes, you can dangle a carrot at the end of a stick for different it’s large enough that different companies that suspect that a drug they’re working on, which could be repurposed, even if it’s off patent, end up paying for trials to confirm that. Then with push funding, you can directly pay for trials with different options, different drugs, that might be beneficial, but haven’t been confirmed or tested yet.

Saloni Dattani: You know, whenever I hear the carrot on a stick idea, I’m always like, who is actually incentivised by this? You know what I mean? Like the metaphor. Who likes carrots enough that dangling it on a stick is actually going to get something to happen?

Jacob Trefethen: Yeah. I think it is either a donkey or Bugs Bunny, I think are the two main sort of actors involved in this incentive scheme.

Saloni Dattani: Yeah. I wonder where that metaphor came from. I always...

Jacob Trefethen: I think it’s mules. Oh, it’s mules. Because it’s carrot or stick. Unfortunately, I think the stick is hitting a mule.

Saloni Dattani: I thought it was a carrot on a stick. Like a fishing rod. Like a fishing rod with a carrot on the end.

Jacob Trefethen: That’s also how I visualize it. It’s like the stick is sort of over the back of the head of this poor mule. Then it’s sort of dangling carrot. Then so it’s walking forward like, I’m going to get the carrot, I’m going to get the carrot.

Saloni Dattani: This is so sad.

Jacob Trefethen: It’s really sad. Some people don’t like to talk about.

Saloni Dattani: Wait, so the carrot doesn’t get eaten at the end. It’s just making them move forward?

Jacob Trefethen: I think they...

Saloni Dattani: That’s really depressing.

Jacob Trefethen: It’s really depressing. I believe in full emancipation for mules.

Saloni Dattani: Me too. You can just use robots or tractors for stuff, no?

Jacob Trefethen: Robots don’t even eat carrots.

Saloni Dattani: No, I mean for the things that you need the mule to do. You were just thinking of dangling a carrot in front of a tractor?

Jacob Trefethen: I’m now just thinking about the humanoid robots and yeah, you just dangle reward. All you have to dangle is a one instead of a zero.

Saloni Dattani: I mean, I do like carrots, but I wouldn’t...

Jacob Trefethen: I wouldn’t go out of my way.

Saloni Dattani: Yeah. I wouldn’t continue to follow this carrot once I realized that I wasn’t getting any closer to it.

We are now at the end of the episode. Let’s do a little summary and some takeaways that we had from all of this chat about GLP-1 drugs, all the other cool drugs that have been approved for multiple things, how it’s possible that things can be used for multiple conditions, and how we can get more of this repurposing done.

Jacob Trefethen: Let’s do it. Let’s start with GLP-1s. What did you think?

Saloni Dattani: I think GLP-1s are much more interesting than I realized. It’s not just weight loss, but they have multiple effects. They reduce blood sugar levels, which helps with diabetes. They suppress appetite and slow stomach emptying, which helps with weight loss, but also causes nausea and vomiting. They slightly reduce blood pressure as well, which might help with cardiovascular diseases. It seems like they might be effective for other diseases too. I think that research is still ongoing.

But what’s amazing about this is that there are actually many drugs like this. Around a third of all FDA-approved drugs are approved for second use. That’s much more than I would have thought. There are some other cool examples that we talked about, like SGLT2 inhibitors, and aspirin and colchicine, things like that have turned out to be effective for something quite important that we wouldn’t have predicted at the start.

The other thing that really stuck with me in this episode was Gila monsters, the lizard. They’re so cool. They’re so cute. I wouldn’t have expected them to look so cute. They’re so slow, which is so funny to me that their top speed is one and a half miles per hour. That’s hilarious. Most importantly for us, beyond the cuteness, they helped us find cool new drug compounds that we could tweak and use for various important health conditions. I think it’s kind of a shame how venomous they are but I think they’re just a very cool type of lizard that more people should know about.

When I started doing research for this episode, I had this vague idea that it was some kind of accidental discovery. It turned out that actually there were important reasons to suspect that something interesting was happening in their venom, that included their effects on the pancreas, and also the fact that they had very long-lasting fasts and they only ate a few meals per year and could control their blood sugar levels despite that.

Jacob Trefethen: I also left this episode a fan of the Gila monster. The fact that even in the deadliest venom, we can find the most wonderful benefits for humanity. There’s got to be a lesson there, which we can leave to the listener.

Saloni Dattani: That’s very moving.

Jacob Trefethen: It’s very moving, slow moving, 1.5 miles an hour. I think that overall stepping- taking the GLP-1 example and then going further to repurposed drugs in general, I left this episode, I would say the pessimism I have is on effect sizes of repurposed drugs. I’m not sure many will turn out to be, stunning radical cures for a second indication. But I left this episode more optimistic about repurposed drugs in general. The fact that for drugs that already have been approved for one thing, you have an existing safety dataset that’s large. The fact that we can point to these economic reasons why companies themselves, wouldn’t be incentivized to pay for confirmatory studies for second indications, and all of that because of competition from generics and how patents work. I think that I am sort of cautiously optimistic there’s low hanging fruit for these beneficial second, third use cases for some drugs.

Saloni Dattani: I also, I think I started out as a skeptic. I sort of thought, well, observational studies are pretty misleading and lots of repurposing efforts are going to fail. Aren’t pharma companies already doing this internally anyway? But I think in doing research on this, I realized actually there are lots of economic reasons why there aren’t the incentives that there could be for doing more repurposing. That’s, as you said, the competition from generics, but also I think some diseases just not being commercially worthwhile to study.

I’m more optimistic about effect sizes, I think, than you are. I think sometimes we’ll have what look like moderate effect sizes, but there’s such a large patient population for them that they’ll be really beneficial. That seems to be true for the aspirin with cardiovascular disease, with colchicine for heart disease, for SGLT2 inhibitors, and for GLP-1s. But to be fair, those were tested commercially, aside from aspirin and colchicine. I think sometimes it’ll turn out that the secondary use is actually pretty big. With GLP-1 drugs, for example, the weight loss was the second use and those have a massive effect size.

Jacob Trefethen: Fair enough. Another thing I took away from this episode is just there are a lot of drugs out there already. Sounds basic to say, but there are thousands or over a thousand FDA approved medicines mostly from the last hundred years and we’re still finding out ways they work, and all the different things they do in the body, at different doses, for different people facing different problems or diseases.

Saloni Dattani: Yeah, it’s pretty cool.

Jacob Trefethen: It’s a bit punk that we don’t even know yet.

Saloni Dattani: I think that’s maybe especially true for the rare conditions or the tropical diseases where just someone hasn’t tried them out or hasn’t tested them. There must be lots of things that we just haven’t found out about yet. What was your favorite repurposed drug that you heard about today?

Jacob Trefethen: I think my favorite is the potential repurposed drug of the shingles vaccine. Maybe it turns out that it reduces your risk of developing Alzheimer’s. So I’m excited about that. But even better, if that ends up being true, I’m excited about me being right and you being wrong.

Saloni Dattani: I really hope you’re right.

Jacob Trefethen: Well you being 75% wrong because you think there’s a 25% chance that I’m right.

Saloni Dattani: Right. No, I really hope you’re right. I wish I could go out and get a shingles vaccine right now, but I am not old enough to. It’s one of those things where, when you’re a kid and you’re like, oh my God, I wish I was old enough to do whatever. Right now I’m like, oh God, I wish I was 50 years old so I could get the shingles vaccine.

Jacob Trefethen: Wow. For me, it was when I was 11. All I wanted to do, we stayed in a hotel once and I, well, probably more than once, but roughly once. They had a gym and I couldn’t go in alone unless I was 18. I was like, one day I’ll be old enough and I’m going to go into this gym. I had to go back to Ohio and then I can go into that gym.

Saloni Dattani: I didn’t know that there were age restrictions on gyms.

Jacob Trefethen: Yeah, I hate to give you such horrifying news this late in an episode.

Saloni Dattani: The other thing that I took away was I didn’t realize how important this was as an issue. I didn’t realize how large this social value of repurposing drugs could be. The estimates that I described, they were conservative estimates that put it at hundreds of billions of dollars in social value per year allowing for more repurposing to happen and under a hypothetical where patent terms were longer.

If you think about, okay, you extend patent terms to get more repurposing, that’s still only going to get you repurposing for diseases that are worth the commercial market. I think that’s still a conservative estimate. It doesn’t include very much like drugs that could be repurposed for tropical diseases, for example. Getting more repurposing could be really valuable. I think we’re missing out on knowing which other conditions many existing drugs might work for. And people need to go and find that out.

Jacob Trefethen: Yeah. One of the things in this episode that I think will stick with me is how much that problem is not scientific, but is about policy, economics, patents, and all of that. Just discussing, okay, how can reimbursement change? When should people run prizes for repurposed drugs? When should you, as a government or philanthropy, use push funding to fund off-patent trials and get more repurposing to happen? I think there’s a lot more activity that could happen in those different areas that would be really beneficial.

Saloni Dattani: I think also what I learned from reading for this episode was just, there are lots of these things already happening. Like there are incentives to some degree for repurposing your drug. You get an extra few years of drug exclusivity and stuff like that. Like, people have tried a bunch of these things already, but we could be doing a lot more of them. What was your favorite idea to get more repurposing to happen?

Jacob Trefethen: I think my favorite one is, honestly, my favorite one is modeling more trials like the RECOVERY trial. You know, have a platform trial, a shared control group, you can make it adaptive as you go. And have lots of off-patent drugs, but companies can chuck in their on-patent drugs too if they want and test things against each other. That is my most exciting takeaway from this episode.

Saloni Dattani: I’m going to disagree with that. I’m going to say prizes, I think, are better.

Jacob Trefethen: Prizes are better than the RECOVERY trial? The best trial of all time?

Saloni Dattani: Maybe not, actually. I think one reason a prize is better is that you don’t have to, as a funder, you don’t have to pick which drugs you think will succeed. Hopefully someone else has some better idea. But also, you could just get other companies to work on funding the trials themselves. You don’t have to pay for that. You can just pay for a prize, which is higher than the cost of one trial, but lower than the cost of funding all the trials. So why not?

Jacob Trefethen: Okay, I’ll meet you in the middle and say, let’s do both.

Saloni Dattani: I guess you do need someone to do both in the end. I guess the other upside of that is that if the drug already exists and it’s already on the market and maybe generics are already there, once you’ve given the prize for it, everyone can use it already.

Jacob Trefethen: True, true.

Saloni Dattani: The last thing that I found interesting was EvE Bio. I thought it was just really cool to have, one, this idea of initiative that is focused on one thing and then will planning to wind down after they finish that one project. But also just scientifically, this idea of testing out lots of combinations of drugs versus targets that haven’t been tested before and then publishing that as an open database that lots of researchers, academics, and pharma companies can use in the future. I think we need a lot more public goods like that and it’s just a really cool example of one.

Jacob Trefethen: Okay, we’ve left this episode with a lot to do. I feel like we both have to get back to work, Saloni.

Saloni Dattani: We should get back to trying out some of these repurposed uses for ourselves.

Jacob Trefethen: You and me volunteering for the sake of science. Each day we can do a different drug and measure what happens to each other.

Saloni Dattani: That’s how a randomized trial works.

Jacob Trefethen: I think so. It’s a shame about immortality bias or whatever you told me about because otherwise I could give all the data we need.

Saloni Dattani: All right. Thank you for listening. I hope you enjoyed this episode. If you did, please rate us on Spotify or Apple. We occasionally get comments on Apple podcasts, but we don’t have that many, so if you could add a comment, that would be really helpful to us.

Jacob Trefethen: Yes. Thank you very much. We would really appreciate that. Feel free to take this episode, chop it up, repurpose it for your own use too. Goodbye!

Saloni Dattani: Bye!

Show notes

Saloni’s substack newsletter: https://www.scientificdiscovery.dev/

Jacob’s blog: https://blog.jacobtrefethen.com/

Acknowledgements:

• Aria Babu, editor at Works in Progress

• Graham Bessellieu, video editor

• Abhishaike Mahajan, cover art

• Atalanta Arden-Miller, art direction

• David Hackett, composer

Blogs

• Julia Rohrer (2018). The uncanny mountain: p-values between .01 and .10 are still a problem https://www.the100.ci/2018/02/15/the-uncanny-mountain-p-values-between-01-and-10-are-still-a-problem/

• Abhishaike Mahajan (2025). Mapping the off-target effects of every FDA-approved drug in existence (EvE Bio) https://www.owlposting.com/p/mapping-the-off-target-effects-of

Videos

• George Davey Smith (2026). Does the shingles vaccine prevent dementia?

Articles & reports

• Radwan Darwish et al. (2025). History of glucagon-like peptide-1 receptor agonists. https://doi.org/10.1016/j.phrs.2025.108045

• Brian L. Furman (2012). The development of Byetta (exenatide) from the venom of the Gila monster as an anti-diabetic agent. https://doi.org/10.1016/j.toxicon.2010.12.016

• Eric Budish, Maya M. Durvasula, Benjamin N. Roin, Heidi L. Williams (2026). Missing markets for innovation: evidence from new uses for existing drugs. NBER Working paper. https://www.nber.org/system/files/working_papers/w34222/w34222.pdf

• Babak Sahragardjoonegani, Reed F Beall, Aaron S Kesselheim, Aidan Hollis (2021). Repurposing existing drugs for new uses: a cohort study of the frequency of FDA-granted new indication exclusivities since 1997. https://pmc.ncbi.nlm.nih.gov/articles/PMC7780607/

• BMJ (2020). Covid-19: The inside story of the RECOVERY trial https://www.bmj.com/content/370/bmj.m2670

• Stephan Guyenet (2021). The future of weight loss https://worksinprogress.co/issue/the-future-of-weight-loss/

• Kevin Hickey, Erin Ward (2024). The Role of Patents and Regulatory Exclusivities in Drug Pricing https://www.congress.gov/crs-product/R46679

• Alex Kesin (2025). The three-thousand-year journey of colchicine https://worksinprogress.co/issue/the-three-thousand-year-journey-of-colchicine/

• Samy Suissa, Laurent Azoulay (2012). Metformin and the risk of cancer: time-related biases in observational studies https://doi.org/10.2337/dc12-0788

• Nicholas Reville (2026). Proposing an NIH High-Leverage Trials (HILT) Program. Center for Addiction Science, Policy, and Research (CASPR) https://caspr.org/policy/papers/HILT/

Web

• Smithsonian’s National Zoo. Gila monster. https://nationalzoo.si.edu/animals/gila-monster

Growing up, I acquired a vague idea that medieval people did not view childhood as we do. I was told they saw children merely as defective or incomplete adults, and that they did not love their children as we love ours, perhaps as a way of coping with high infant mortality. As I grew older, I came to associate this idea with the name of Philippe Ariès, a French historian who argued in the 1960s that medieval childhood was profoundly remote in these ways. Ariès’s work never attained complete acceptance in academia, but it was vastly influential on the wider public.

As it turns out, however, Ariès’s view is just not true. This has been established beyond doubt by a wealth of later scholarship across Europe. Nicholas Orme’s Medieval Children is the leading study for England in particular. ‘It cannot be overemphasised that there is nothing to be said for Ariès’s view,’ Orme notes. It is mistaken ‘not simply in detail but in substance. It is time to lay it to rest.’

It is sometimes imagined that medieval people had a great many children. This was not generally the case. Very large families occasionally occurred, but most medieval people had only three or four children, somewhat more among the rich and somewhat fewer among the very poor. At least in England, this was partly because they married quite late, generally in their mid or late twenties. About 25 percent of children died in their first year and another 15 percent by their tenth. The median English child thus grew up in a home with one sibling and two parents in their thirties or forties, being in this respect just like the median English child today. Surviving grandparents often lived nearby, but rarely under the same roof.

Abortion was considered sinful, but the situation was more complicated than might be supposed. Medieval people did not think that early-term fetuses had souls, believing them to be alive but unconscious, like vegetables. Early-term abortion was thus not considered homicide, and was not punishable at common law, though a church court might impose a penance like regular fasting or almsgiving. Late-term abortion was thought to be a kind of homicide, but was not normally punished at common law either. This distinction persisted until the nineteenth century.

Medieval parents made immense sacrifices for their children, and seem to have expected little in return. Feeding a child consumed about 15 percent of average income, and parents often continued to support children throughout their adulthood. Older children often performed light work at home, but at just the age they might become a net economic asset – 13 or 14 – they were usually sent away to acquire skills and savings through apprenticeship or working in service. They may have remitted some of this income to their parents, but this was not standard, and in fact parents generally paid for their children’s apprenticeships. Grateful children sometimes supported their parents in old age, but again this does not seem to have been the norm.

Medieval England was often at war, and the government was desperately in need of soldiers. The Crown repeatedly issued decrees banning ‘dishonest and useless’ ballgames like football, requiring boys over the age of seven to practice archery instead. Needless to say, English boys could not be stopped from playing football, and the decrees were widely ignored.

Child mortality was high, but there is no reason to think that parents were indifferent to it. Few diaries or letters survive in which they expressed their grief, but it was sometimes recorded by others. The fifth child of Henry III and Eleanor of Provence was called Katherine. Katherine was born disabled and never learned to speak, and she died when she was three years old. Both her parents were heartbroken. The chronicler Matthew Paris wrote that Queen Eleanor fell sick with grief, ‘and could find no relief in medicine nor human consolation’.

Parents also took joy in their children, and vice versa. An Oxford schoolbook of the 1490s describes a schoolboy returning home for the holidays. Upon meeting his parents, ‘we wept for joy, each to other’. The thirteenth-century treatise Ancrene Wisse imagined Jesus playing with a Christian believer as a mother does with her child. ‘She runs away from him and hides herself, and lets him sit alone and look anxiously around, and call “Dame! Dame!” and weep a while. Then she jumps out laughing, with outstretched arms, and embraces and kisses him and wipes his eyes’.

The medieval people who emerge from Orme’s book are quite unlike the strange and cold figures that we have been led to imagine. ‘I believe they were ourselves, five hundred or a thousand years ago’, Orme writes. Perhaps we should ask why the Ariès hypothesis ever exercised such a hold over the popular imagination. Was it ever really plausible that children survived the terrible hardship of medieval life without devoted parents? Next time a scholar makes exciting claims about how some class of human beings is incomprehensibly unlike us, we would do well to ask similar questions.

Samuel Hughes is an editor at Works in Progress.

This piece was featured in Issue 24 of Works in Progress. Subscribe today to get Issue 25, and an issue every two months after, delivered straight to your door.

Ultra-Orthodox Jews may have something to teach us. They live squarely in the urban centers of the US and Europe, including 200,000 in New York City, but unlike most city dwellers, they have very high birth rates. Today, a Yiddish-speaking woman in the United States can expect to have 6.6 children, compared with 1.6 for the country as a whole.

Everything in ultra-Orthodox life is geared toward facilitating large families, from how children play to how couples have sex. In this piece, I’ll use the example of Chabad, the largest denomination of Hasidic Jews, although many practices mentioned here are shared by all the ultra-Orthodox.

It’s not clear that many modern people, Westerners or not, would want to adopt the family-friendly elements of Chabad life. What’s more, little of the Chabad lifestyle can easily be practiced in isolation. But understanding how this community encourages fertility can help to explain why it is falling in many other parts of the world today.

Share

Before marriage

1. Chabadniks start having children young: there’s almost no way to have six or more children if you’re starting after 30. Yiddish-speaking men in America have a mean marriage age of 22 and women 21, and couples will almost always have children shortly after, partly because contraception is broadly discouraged.

2. Since lifetime mates are chosen at a young age, Chabadniks believe the selection can’t be left to the couple alone. I don’t mean to be rude, but 18-, 19-, and 20-year-olds don’t have a reputation for great judgment in any area. Even so, Chabadniks would object to characterizing the way they date as ‘arranged’, but from a secular point of view, the level of parental and community involvement and the short duration of courtship make Chabad dating practice resemble arranged marriage.

3. Chabadniks segregate children and teens by gender, believing that it helps to make their short courtship with a small number of potential partners feel satisfying and selective. Teenagers can’t have boyfriends and girlfriends in middle school and high school, and children are forbidden from playing at the marriage experience. Even in my secular Jewish childhood, our Hebrew school teachers scared us with tales of rabbis who made children get real divorces after pretend weddings.

4. Sex before marriage is prohibited. Such restrictions have long been foisted inappropriately on American teens, but they are much less unreasonable when community members marry around 20.

After marriage

Starting early isn’t enough to guarantee many children. Parents need to have kids young and then continue to have them throughout their twenties and thirties. But how do couples continue to like each other enough to keep wanting to have more children (including having the frequent sex this requires)?

1. Gender segregation continues in many, if not most, areas of adult life. This helps maintain a sense of romance in daily life. As the Chabad-Lubavitch website says: ‘If we preserve the space and boundary between men and women we can cherish our times of closeness all the more’.

2. Men and women are prohibited from mixing because rabbis believe a love affair is around every corner. But the omnipresence of assumed temptation both makes extramarital affairs difficult and, according to Chabadniks, creates the sensual atmosphere it’s meant to dispel, while channeling it toward the only acceptable outlet: one’s spouse.

3. Sex becomes a pious act, permitted within a limited timeframe. While a woman is menstruating, and for the seven days after the end of her period, a couple doesn’t have sex at all. Some couples take this very seriously and won’t even touch lest contact lead to physical intimacy. This even includes handing each other an object in case their hands touch accidentally. At the end of this period, the woman goes to a ritual bath called mikvah. The mikvah visit happens at night, when the sun is down, and the bath is a communal facility, some of which are quite fancy. Upon returning home, the woman is supposed to have sex with her husband. Having sex on day 12 or 13 of her menstrual cycle is a great way to maximize the chance of conceiving!

4. Sex is especially encouraged on Shabbat, the Jewish day of rest. From Friday sundown to Saturday sundown, pretty much all that’s permitted is eating, praying, reading, socializing in your neighborhood, and napping. The faithful are commanded to enjoy Shabbat, and one of the recommended ways is to have sex with one’s partner. As one prominent halachic code (a compilation of rabbinic law) says: ‘Marital intimacy is one of the expressions of Shabbos pleasure’.

The life of a child and its parents

The gender segregation described above may seem alien, but we seculars also inhabit segregated worlds; they’re just not tied to our biological sex. We call them ‘professional’ and ‘leisure’, ‘public’ and ‘private’, or ‘adult’ and ‘child’.

In fact, people without children may not realize how totally we separate children into their own sphere and complicate their existence outside of that sphere. Not only does this discourage adults from having children, it also marginalizes those who do have them, especially women.

When children are permitted in public spaces, the expectation is that they be continuously and closely supervised by an adult, in a bubble of attention and control. A recent poll of five hundred children between the ages of eight and twelve found that 62 percent had never walked or biked somewhere without an adult. Even in the absence of actual danger and even when they’re not causing a nuisance, children are not allowed to roam, with parents sometimes facing prosecution when they leave their children unsupervised.

While Chabad life has gender segregation, the separation between adult and child spaces does not exist in the same way. Children are considered a blessing, and making it easy to raise them is a major purpose of life.

Walking into a Chabad congregation, one of the most surprising features for secular Americans might be that young children roam anywhere in the building apparently without limitation, playing games, squealing, and laughing, including at the front of the room where the service is being led. A leading Chabadnik rabbi, Zushe Greenberg, explains: ‘We not only recruit kids to come to shul [synagogue], but even encourage this phenomenon. As I always tell people, we allow the adults at Chabad because they’re the ones who bring the kids’. Some of these children belong to the rabbi. He might pick one up, or shush them in passing. If they’re very loud in the hallway, other congregants might shush them too, but children making noise or playing unattended in this space isn’t problematic. Rabbi Elisha Greenbaum says: ‘A shul without children is boring. What kind of organization would deliberately reject their own future and opt for a sterile, boring, child-free environment?’

Lastly, Chabad women do not carry the burden of childcare alone. Men and older male children are active contributors to childcare and to children’s education. Religious men, in general, do more housework and more childcare than non-religious men. And communal childcare is the default. In New York, for example, many more Orthodox Jews, including Chabadniks, send their children to daycare than non-denominational Jews do: 54 percent versus 15 percent aged 0–2 and 93 percent versus 18 percent aged 3–5. Nursery schools are run and staffed by women, but primary schools for boys have male teachers and leadership to a great extent.

Subscribe now

Learning from Chabad life

Copying Chabad life wouldn’t be easy in secular society. Religious belief adds weight to practices like the mikvah or sexual abstinence. But there is one pronatalist practice that we can adopt from ultra-Orthodox life and that all high-fertility subcultures share: assuming that everyone you interact with between the ages of 20 and 45 will have at least one child under five in their care. This assumption impacts every social and business function. Children are welcome in far more spaces, and where they aren’t, event organizers provide schedules and resources to facilitate the participants’ childcare needs.

This might seem like a tall order, but in the developed world we already expend tremendous consideration and public resources for a type of dependent: people’s cars. The host of an event, the owner of a store, the developer of offices or housing, an employer, or a local government will all assume their guests, customers, tenants, employees, and residents have cars, and take responsibility for providing a place to store and a convenient way to transport them.

We take on tremendous expenses to build huge parking garages and wide and smooth roads for people’s cars. This social support incentivizes driving. If we extended as much concern for people’s children as we do for their cars, we would, like Chabad, encourage more children than we have today.

Sonja Trauss is the Executive Director of YIMBY Law.

Some of America’s most famous land was reclaimed from the sea. The Lincoln Memorial, the World War II Memorial, and the Reflecting Pool all sit on earth reclaimed from Potomac River tidal flats in the early twentieth century. Treasure Island was built in San Francisco Bay for the 1939 Golden Gate International Exposition. Chicago’s Northerly Island was filled in from Lake Michigan to complete Daniel Burnham’s 1909 plan of the city.

In total, around eight percent of the land in America’s major coastal cities was underwater in the 1890s and has since been reclaimed. This includes the land under several major airports, like Newark, Logan, and SFO, as well as neighborhoods like the Financial District in San Francisco, the Back Bay in Boston, and Camden in Philadelphia. Some cities, like Boston and Charleston, have doubled in size by reclaiming land.

Today, reclamation should be more common than ever. Land values in some cities are thirty times what they were in 1950, and high-tide flooding is four to eight times as frequent. Reclamation could extend and protect our coastal cities as it has for centuries. But rather than reclaim more land, we have virtually ceased to reclaim any at all. Since the completion of Battery Park City in 1976, there has not been a single major urban land reclamation project in the United States and only a handful of port expansions.

Subscribe now

Two explanations are commonly proposed for this: first, that the easy spots have already been reclaimed, and second, that improved transportation has made reclamation unnecessary since we can expand cities further inland instead. But neither of these matches the evidence. Other countries still reclaim land at enormous scale, under conditions at least as challenging as those in the United States. The transportation story was once plausible, but not any more. Transportation has stopped improving, and downtown land values have risen so much that reclamation costs would be dwarfed by the value of the land created.

The timing points to a third explanation. Reclamation stopped abruptly in the 1970s when a wave of environmental regulations made it enormously expensive to reshape the landscape. And it halted at the same time in every other country that passed similar laws.

If the legal barriers to reclamation were lifted, we could build hundreds of thousands of new homes near the centers of our most valuable cities. We could build new airports to refresh ailing transportation infrastructure, and we could protect low-lying coastal areas from sea level rise. The disappearance of land reclamation is a choice that we have the power to undo.

Have we run out of good spots?

A common explanation is that we simply ran out of good places to reclaim. According to this view, there used to be plenty of shallow, semi-dry plots available, but they’ve mostly been used up.

There are indeed a finite number of shallow bays near major cities, and since land is often raised in one area by dredging the bottom of the surrounding waters, land reclamation can eat into its own expansion opportunities. But even so, many countries have been adding land for centuries without running out of good options. China has the longest reclamation history of any nation, stretching back to the Tai Lake Basin in the fifth century BC. Low-lying wetlands along the Yangtze river were made suitable for building by using dams and drains. If the US hit the limit of suitable areas for land reclamation within two centuries, China would surely have long since run out, having begun the practice over two thousand years ago.

Subscribe now

But China still leads the world in land reclamation, with close to 80 percent of all land reclaimed in the twenty-first century. Since 2000, Chinese cities of over one million people have reclaimed a land area equivalent to 39 Manhattans, with even more reclamation occurring outside city limits.

American history argues against this theory too: reclamation wasn’t confined to a few choice spots in the most valuable cities. It was common along both coasts, even in smaller cities like Charleston, Wilmington, and Portland.

Hundreds of square miles of water near major American cities are shallow enough to reclaim easily. When Boston’s Back Bay was filled in the late-nineteenth century, it had an average depth of 20 feet. Two thirds of the San Francisco Bay is shallower than this. The South Bay, adjoining Silicon Valley, is less than six feet deep. Outside the main navigation channels, most of New York harbor is less than ten feet deep. Almost all of the water between Miami and Miami Beach, and along the shelf extending south to Key West, is also less than ten feet deep. All of these could be candidates for reclamation.

Nor is depth a hard limit if land values are high enough. Monaco’s recent Mareterra project expanded the country’s land area by three percent by dredging down to 164 feet.

Soil and rock conditions also matter, but much of the American coastline has better conditions than sites where reclamation has already succeeded. Singapore’s Jurong Island is a massive industrial zone created on land reclaimed between 1995 and 2009. The water was more than 50 feet deep and atop another 50 feet of soft marine clay, which settles more than other materials under pressure. To reclaim the land, these layers had to be threaded with long plastic tubes to allow drainage and loaded with a large, heavy quantity of extra soil.

Subscribe to print

It is possible that the United States could eventually exhaust its opportunities for land reclamation. But given how much further other countries have gone and how much suitable coastline remains, that point is likely a long way off.

Has transportation made land reclamation unnecessary?

Another explanation is that land reclamation was replaced by transportation. When walking was the main mode of travel, cities faced tight spatial constraints. Boston began as a tiny peninsula of about two square miles. The city quickly outgrew its isthmus, but land to the south was too far for commuters to walk from. If Bostonians wanted to build close to the city center, they had to expand into the sea.

Other cities faced the same problem even where land was more abundant. In 1890, while Manhattan’s population was similar to today’s, there were still farmhouses beside Central Park, only six and a half miles north of Wall Street. The need to build within walking distance of the city center made northern Manhattan effectively unusable, justifying extensions to the southern tip. Even with plenty of dry land available, the city kept filling in riverbeds and marshland around the island. In all, over a quarter of Manhattan’s land was reclaimed before 1979.

Over time, however, land reclamation became less useful. Better transportation unlocked lots of greenfield land that was cheaper to develop than dredging up new land from the water, while the elevator unlocked brownfield land from the sky.

This abundance of new land within the commuting zone of cities was a cheaper substitute for reclaimed land. Boston’s Back Bay reclamation in the 1860s cost about $400,000 per acre in 2025 dollars. Although the state of Massachusetts ended up selling the land for a healthy profit, by the 1910s there were cheaper ways to unlock land within reach of the city center. If each of the 332 stations of New York’s 1913 subway extension connected a half-mile radius to the downtown, this form of land reclamation cost only $65,000 per acre in 2025 dollars, five to ten times less than land reclamation from the sea.

Subscribe now

But this alternative source of land has proven difficult to extend indefinitely. First, while there may be land that we can access by expanding our cities outwards into virgin countryside, doing so is politically tricky in most countries, not least the United States. Adding more New York suburbs in New Jersey and Connecticut would mean a modern Robert Moses building more expressways through Manhattan.

Second, with enough population and economic growth, even the vast swaths of land accessible by modern transportation can eventually be filled. The edge of New York’s metropolitan area is already 40 miles from Midtown Manhattan at many points, over an hour’s commute. After rapid improvements in the twentieth century, transportation technology has stagnated. Average commute times have increased by a quarter since 1980, partly because cars haven’t grown much faster and partly because highway construction costs at least four times as much per mile as it did in 1960.

Finally, reclamation adds space near city centers, where land is far more valuable than at the suburban fringe. Cities are valuable because they concentrate economic activity, making it easier to find jobs, customers, and suppliers, and because they generate knowledge spillovers making everyone more productive. Better transportation increases their value by putting more workers, suppliers, and customers within reach. Crime and pollution pushed people out of city centers in America after World War II. But since 1990, this trend has reversed, and the value of land in city centers has grown quickly despite continuing suburban expansion.

Today, downtown land values are high enough to justify reclamation costs even in places where suburban land is plentiful. In 1955, the California Division of Water Resources estimated that reclaiming 23,000 acres of land on the west side of the San Francisco Bay would cost about $330,000 per acre in 2025 dollars. Today, the cost of an acre of single-family-zoned land in San Francisco County averages $24 million, more than 70 times the estimated reclamation cost. Even the cheapest county in the Bay Area exceeds $330,000 per acre.

Subscribe to print

Despite the space opened up by cars, trains, and buses, America’s biggest cities face a massive land shortage. Even as the transportation explanation has weakened, reclamation hasn’t returned. Boston’s Back Bay reclamation was profitable when land sold for the equivalent of $40 per square foot. Land in major cities today sells for ten to a hundred times that, and dredging capacity has grown nearly tenfold since 1950. Yet urban reclamation has disappeared even in the most land-constrained cities in the country.

How reclamation went extinct

Neither explanation is convincing, especially where urban land values would plainly justify reclamation. But there is another problem: the explanations cannot easily account for the timing of land reclamation’s disappearance. A technological or geographic explanation would predict a slow and patchy decline, as different regions responded to different pressures at different speeds. But this is not what happened. In the 1970s, reclamation stopped virtually simultaneously everywhere in the country.

Of the 37 cities for which we can find data, every one reclaimed land more slowly after 1970, with many, such as Seattle and Chicago, slowing to zero. A few, including San Diego, Washington, and New York, do show some growth in land area after 1970. But most of this reflects changes in measurement or the completion of projects already underway.

The abruptness of the change shows up clearly in data on the amount of wetland that is lost per year. Most wetland loss is inland and agricultural, not the coastal urban reclamation we’re advocating. Still, the aggregate trend makes it clear that land reclamation ended suddenly around the 1970s. The annual rate of wetland loss in the 1960s was eight times higher than in the 1990s, and twenty times higher than in the 2010s.

In the 1970s, the United States passed a wave of new environmental laws, with perhaps the most far-reaching effects on land use in the country’s history: The National Environmental Policy Act of 1969 (known as NEPA), the Endangered Species Act of 1973, the Clean Water Act of 1972, the Marine Mammal Protection Act of 1972, the Resource Conservation and Recovery Act of 1976, and others. These laws hit the whole country at once, enormously raising the cost of reshaping the landscape, and are the real explanation for the end of American land reclamation.

Still in force, these laws largely regulate the federal government and not private development. But the moment a private project touches federal land, funding, or permits, it must comply with all of them. For land reclamation, NEPA is the most onerous.

NEPA requires covered projects to prepare a detailed report on the environmental impact of the proposed action and its alternatives. While NEPA itself sets no standards for how detailed these reports must be, decades of litigation have turned them into thousand-page behemoths that take years to produce. The environmental assessment for New York City’s congestion pricing plan, for example, is 900 pages long with 3,000 pages of appendices, despite the project requiring zero major construction. When potential harms are identified, agencies must undertake mitigation: buying and restoring 3,000 acres of panther habitat, say, or donating $16 million to conservation banks. In some cases, the project is simply blocked.

Subscribe to print

Land reclamation must always go through the NEPA procedure because the Clean Water Act requires a federal permit for any discharge of dredged material into waterways or wetlands, including the entire coast. Because land reclamation projects do have significant environmental effects, every project must either complete a full environmental impact statement or produce an environmental assessment with costly mitigation measures before receiving a permit. Environmental impact statements filed by the US Army Corps of Engineers, the agency that oversees the permits for land reclamation, take an average of six years to complete, and the mitigation measures often run into the hundreds of millions of dollars.

The Craney Island extension in Norfolk, Virginia is a useful illustration of how these laws complicate land reclamation. Craney Island is a four-square-mile rectangle of dirt and sand surrounded by dikes at the mouth of the Elizabeth river, built solely to store material dredged from Chesapeake Bay navigation channels. In 1997, Congress approved a study of the possibility of expanding the island to the east, extending the lifespan of the disposal area and adding a container shipping terminal to the Norfolk port.

By historical standards, this would have been an easy project: the original 2,500-acre Craney Island was built in just two years between 1956 and 1958. But because the extension involved discharging dredged material into US waters, it needed a Clean Water Act permit. The Army Corps’s environmental impact statement took nine years and ran to 1,400 pages.

Virginia’s environmental quality department then issued permits in 2010, three years after the environmental impact statement was published. After a decade of delays and budget uncertainty, the Corps changed its discharge plans in 2023, which required yet another supplemental environmental assessment. Twenty-eight years after the feasibility study began, almost nothing has been built. The project is expected to finish ‘on schedule’ in 2065.

Craney Island is not an isolated case. Land reclamation ground to a halt across the country after the major environmental laws passed in the 1970s. Very few US reclamation projects started later in the twentieth century, and no notable urban reclamation projects have taken place in the twenty-first.

Evidence for environmental law’s role in the end of American land reclamation can also be found in other countries. It declined abruptly in the 1970s and 1980s across the West. What western nations shared was the rise of powerful environmental movements hostile to reshaping the landscape.

Germany reclaimed over 80,000 acres from the marshy Wadden Sea before 1990. Tens of thousands more were planned, but fierce environmental opposition ended the practice in the late 1980s, turning the Wadden Sea into a national park and making wetlands protected areas. In the 1960s, France used reclamation to develop its Mediterranean coast into a world-class tourist destination, but environmental protection laws in the 1980s banned all construction within 100 meters of the shore.

Subscribe to print

In the early twentieth century, Canada reclaimed tens of thousands of acres of floodplain in British Columbia and the Maritimes, along with hundreds of acres of urban land in cities like Toronto, but large projects like these have stopped or greatly slowed due to environmental rules. In nineteenth-century Australia, hundreds of acres were reclaimed in Sydney Harbor, including the land under the Sydney Opera House, but twentieth-century environmental rules have prevented future expansion.

Even the Dutch, history’s most celebrated reclaimers, largely ceased the practice after the passing of their own environmental laws. From about 1917 to 1970, the Dutch undertook the largest reclamation project in history: the Zuiderzee Works, which expanded the Netherlands by five percent. The fastest phase, the 1927 Wieringermeer Polder, dammed and drained 50,000 acres in just three years. The 1957 Eastern Flevoland Polder then reclaimed nearly three times the area in less than eight years.

But only four of the five planned polders were filled. The fifth, the Markermeer, which was dammed and ready to drain in 1975, was never completed. It would have provided the closest land to Amsterdam, where house prices have risen 120 percent since 2010. In 1969, the Netherlands created a new approval process for large spatial planning projects similar to the NEPA. This process required extensive public consultation and referendums which, while not as explicitly environmental as NEPA, were still dominated by environmental concerns. While the debate dragged on, the 1979 European Birds Directive added another layer of environmental protection. Environmental groups campaigned to halt reclamation permanently and have the unfilled lake designated a Special Protection Area.

In response, the government eventually abandoned its land reclamation plan. In 1992, the Markerwaard was listed as a protection area, preventing any development on some of Europe’s most valuable water. (Some reclamation has resumed since 2014, but not for people: a €300-million, decades-long project is building swampy archipelagos in the lake as bird habitat).

Even the rare successes are instructive. The one major Dutch reclamation of the twenty-first century, an expansion of the port of Rotterdam called Maasvlakte 2, took eighteen years to complete, including an eleven-year planning and environmental compliance period before construction began. Its environmental review alone ran to some six thousand pages.

Reclamation has continued only in countries where environmental regulation is less onerous, like China, Singapore, and Japan. China has reclaimed over 5,000 square kilometers in the first two decades of this century, including a new city of 500,000 outside of Shanghai, and Singapore has expanded its territory by over a quarter since 1975.

Japan does have high environmental standards and a NEPA-style law requiring environmental impact reports. But Japan’s system has two advantages: clear numeric thresholds for when reports are required and courts that make it harder to overturn agency decisions. Japanese infrastructure projects don’t need the defense against legal challenges that make Western projects take decades. The result is abundant housing and infrastructure, including multiple airports, port facilities, and residential areas built on reclaimed land.

Subscribe to print

Land reclamation has always faced obstacles, and the story of its historical fortunes is not simple. But the weight of the evidence points in a clear direction. In America, as across the West, land isn’t reclaimed today because of barriers of geography or technology, but because 1970s environmental regulations made it prohibitively expensive and slow.

The wrong solution for an old problem

Reclamation would be feasible and profitable in the West today if some environmental laws were changed. But those laws were passed to solve real problems. So is it worth bringing land reclamation back?

The postwar state had incredible power to act unilaterally and grade its own work. Robert Moses could demolish entire neighborhoods for expressways without accountability; urban renewal programs replaced them with awful housing blocks; the Cuyahoga River caught fire from wanton industrial pollution; the interstate highway system demolished half a million homes to make way for highways through urban areas; and indeed land reclamation was sometimes responsible for the loss of valuable wetlands. These excesses understandably created fear of unchecked development.

Environmental laws provided necessary curbs, but since the 1970s, the costs of compliance have grown as NEPA reports expanded from ten pages to thousands and spurred half a century of expensive litigation.

Simultaneously, the value of foregone construction has never been higher. Real housing prices are at least five times higher today than in 1970 in New York, San Francisco, Boston, and LA, and three times higher across the country as a whole. Land reclamation may be the most striking casualty of 1970s environmental law. Land reclamation makes housing cheaper, cities more productive, and transportation networks more efficient. It also addresses twenty-first-century environmental challenges: city dwellers produce far less carbon per person than suburbanites, and reclaimed land can make coastal cities more resilient to natural disasters.

Subscribe to print

Despite the environmental costs, there are many places in the country where the benefits of land reclamation are too great to ignore, in particular in and around our biggest cities. In some cases, the environmental benefits of bringing more people into dense, efficient cities where they have far lower emissions per capita may outweigh the loss of aquatic habitat all on its own, leaving the direct benefits of more land as pure reward.

Land reclamation is not the solution to everything, but there’s no good reason we should be worse at land reclamation than we were 150 years ago. There is plenty of land that is easy to reclaim and plenty of areas where the value of land is far greater than the cost of acquiring it. The benefits of more land in our most productive cities are large enough to justify the effort of reforming the laws that currently prevent it. Let’s make more land!

Zigmund Forrest is an independent researcher. Maxwell Tabarrok is a graduate student at Harvard University.

Artwork by Filip Setmanuk.

The holy grail of cancer therapy. Roughly half of all cancers have a mutation in p53, one of the most important proteins in our body. It protects us against cancer by acting as a checkpoint: when a cell’s DNA is damaged, p53 can pause the cell to help it repair the damage, or trigger the cell to self-destruct before it becomes cancerous. Destroying mutant p53, or restoring the function of healthy p53, has therefore been something of a holy grail in cancer therapy.

So far, though, it has been incredibly hard to develop drugs against mutant p53. That is partly because p53 can carry a wide variety of possible mutations, and partly because mutant p53 proteins tend to be slippery, without an obvious pocket where a drug could bind.

A new paper by Jennifer Doudna’s lab, which pioneered CRISPR/Cas9 as a gene-editing technology, describes a new approach. Rather than trying to attach to and block the protein, why not kill cancer cells that carry the mutation? So they developed a system to do that, CRISPR-Cas12a2. It finds mutant RNA transcripts of p53 and switches into a destructive mode, shredding the cell’s DNA, which essentially causes the cancer cell to commit suicide.

The guides are highly specific: they target just a single-letter change in the RNA and leave other cells as they are. They are delivered as mRNA inside lipid nanoparticles, with components that steer them toward the lungs, unlike the standard lipid nanoparticles that tend to be taken up in the liver. And helpfully, the nanoparticles can carry several guides at once, so one treatment could target multiple p53 mutations or cancer-causing genes together.

Subscribe now

The first base-edited human embryo. Eight years ago, the Chinese scientist He Jiankui became infamous for using CRISPR-Cas9 to edit embryos from IVF that became children. This was more than an ethical scandal about gene-editing. The standard CRISPR-Cas9 system he used is technically risky: it cuts through both strands of DNA while making the edit, and since the break is hard for our cells to repair, it can result in losing long stretches of DNA or even entire chromosomes. Dieter Egli, a scientist at Columbia, tried it in a research setting in 2020 and found around half the embryos suffered from what he called ‘catastrophic consequences’.

Now, Egli’s group has tried another, safer approach, in the lab: base editing, which cuts only one strand of DNA instead of both, and replaces just a single letter of DNA. For certain mutations, this kind of single letter edit is enough to make a fix. The team base-edited two genes in donated embryos: PCSK9 (which regulates cholesterol levels) and HBG (which controls fetal hemoglobin), and found the edits were both efficient and free of causing the chromosomal damage seen with Cas9. But, the edited embryos weren’t implanted as He Jiankui had done.

The method resulted in some rare off-target edits, with segments aside from those of interest being edited too. And it wasn’t fully effective, as many embryos came out as genetic mosaics, with only some cells carrying the edits. (The phenomenon of being a genetic mosaic is also seen in rare cases in humans. It’s called ‘whole-body chimerism’, from two separate embryos merging into one, early in development. It’s mostly harmless and often discovered only by accident, during DNA testing, though some people with it have noticeable features like patches of differently colored skin or eyes.)

Although the technology is still in development, the idea could correct the single-letter mutations that cause many congenital diseases. Embryos found to carry such mutations during IVF, which parents might otherwise discard, could instead be repaired. Scientists have also been working on gene-editing technologies that could be applied ‘in utero’, not just during IVF, meaning gene-editing could correct congenital mutations that cause diseases like cystic fibrosis, but before birth, as fetuses grow.

The first CRISPR medicine, three years on. A few years ago, the first CRISPR medicine was approved: Exa-cel (exagamglogene autotemcel). It’s a gene-editing therapy for sickle cell disease and beta thalassemia. Both are inherited disorders of hemoglobin (the protein that red blood cells use to carry oxygen) and in both cases, the blood ends up carrying less oxygen than usual. Until recently, the only cure was a stem cell transplant from a healthy donor, but suitable matches are hard to find and transplants carry risks.

To solve the problem, the CRISPR medicine works by switching a fetal form of hemoglobin back on. People make this fetal hemoglobin naturally before birth and then switch to the adult form, and it carries oxygen just as well. In the therapy, doctors remove a patient’s blood stem cells, switch fetal hemoglobin back on with CRISPR-Cas9, clear out the remaining stem cells with chemotherapy, and then return the edited cells to the body.

A new paper reports the results of two phase 3 trials of exa-cel in children aged 5 to 11. Most children in the study were, in effect, cured: those with beta thalassemia no longer needed blood transfusions, and those with sickle cell disease became free of the painful episodes of blocked blood vessels; the remaining children hadn’t been followed up for long enough to tell. The result has led the FDA to expand the treatment to children as young as two.

But it’s a hard therapy to go through, with side effects that can be fatal. Every child in the trials had serious side effects from busulfan, the chemotherapy used to clear the bone marrow before the edited cells go back in; two developed liver disease, and one died. The edited cells themselves weren’t harmful but the process to clear out their original cells with chemotherapy, unfortunately, was. It doesn’t have to be this way: new technologies that could skip the chemotherapy step and directly edit cells in the body are in the pipeline, though they’re currently early in development.

Subscribe now

Lab-grown human eggs and sperm (with caveats). Two separate biotech companies – Paterna Biosciences and Conception Biosciences – have reported growing human sperm and immature eggs, respectively, in the lab.

The companies are trying to achieve ‘in vitro oogenesis’, or IVG, a technology in which adult skin or blood cells are ‘reprogrammed’ back into pluripotent cells, and then coaxed to form viable eggs or sperm.1 So far, this technology has only worked in mice, with just 1–3 percent of lab grown eggs leading to viable pups. If IVG ever works for humans, though, it would mean that just about anyone who wants to have biological children could do so, including two men or two women, or women who don’t have many eggs of their own.

How about men who lack sperm? About 10 percent of men with infertility, and about 1 percent of all men, have something called ‘azoospermia’, which means they have zero detectable sperm in their ejaculate. The condition can be caused by an inability to make sperm at all, or by a blockage where sperm fail to exit the body. Paterna, one of the biotech companies working on IVG, claims to have developed a technology that would solve either problem by isolating sperm-making stem cells directly from a patient’s testicles, via a biopsy, and then coaxing them into developing mature, functional sperm in a dish. These lab-grown sperm were able to create human embryos that appear healthy, though further testing would be required to find out if the embryos had any genetic (or epigenetic) abnormalities.

The holy grail in the field, though, would be to make viable eggs or sperm all the way from blood or skin cells taken from the body, after converting the latter into pluripotent stem cells. Paterna did not do that: they are using stem cells from the testes that already have the ability to make sperm inside the body, and then recreating those sperm-making conditions outside the body.

As for the eggs, Conception Biosciences, based in San Francisco, says they’ve ‘generated the first early human egg cells (‘primary oocytes’) derived from stem cells.’ The company writes: ‘After performing a simple blood draw, we converted blood cells into stem cells, and then coaxed those stem cells into becoming miniature human ovaries that contain the early eggs.’ Note that they are only claiming to have made early eggs, which are immature, rather than mature eggs that could be used to make a human embryo.

Neither claim has been published, and experimental data is scarce. But people we’ve talked about this with in the reproductive technology field say their claims are likely real, even though it’s not clear whether either could lead to a viable pregnancy.

The race to cure multiple myeloma. Treatment for multiple myeloma, a cancer of the plasma cells in the bone marrow, has advanced a lot over the years. Much of this progress has been down to antibody treatments that direct the immune system to fight the cancer. Some, like daratumumab, tag myeloma cells so the immune system destroys them. These treatments are grueling, though: they have to be taken continuously, they carry real side effects, and in many patients the cancer relapses eventually.

Ruxandra Teslo and Amol Punjabi recently wrote about a big breakthrough from another angle: CAR-T cell therapy, where a patient’s own T cells are removed and re-engineered to hunt the cancer. The standout, Carvykti, was developed in China, and is a cure for some. About a third of patients in the phase 3 trial, with relapsed or refractory multiple myeloma, were still disease-free five years after a single infusion, with no further treatment.

But the off-the-shelf antibodies are fighting back. Talquetamab is an example. It’s a ‘bi-specific’ antibody, which grabs myeloma cells with one arm and T cells with the other, and bridges them, helping the patient’s own T cells kill the cancerous cells. It’s been approved since 2023, but only for patients who have already been through at least four prior treatments. Now a new phase 3 trial suggests it can be given much earlier, after a first relapse.

How well does it work there? Very well! Added to daratumumab, it cut the risk of the cancer progressing by two-thirds against a standard regimen (with roughly 78 percent vs 52 percent of patients were progression-free at two years) and halved the risk of death within two years.

Subscribe now

Electron microscopes with laser beams 100 million times brighter than the surface of the sun. Electron microscopes can help visualize objects far too small to be seen through regular light microscopes, including individual proteins. They work like this: a ‘gun’ fires electrons down a column, and magnetic lenses focus them onto a thin sample. The electrons hit the sample, scatter off, and collide with a detector, which then generates an image.

This approach has a few problems, though. For one, it only works under vacuum, so researchers must kill cells before imaging them. Even the remaining material gets ripped up and slowly destroyed by the electron beams over time. And transparent things, including cells, barely scatter the electrons passing through, so most images look blurry.

When electrons pass through a specimen, they split into two populations: most pass straight through, but a small fraction scatter, shifting their wavelength by one-quarter. At the detector, these two populations of electrons overlap and interfere, and the sum of the ‘heights’ of their waves determine the final brightness of the image. Since waves that are a quarter-wavelength apart add up at nearly right angles, the electrons scattered by the specimen have almost the same brightness as the background, which means minimal contrast.

Now, researchers at UC Berkeley have taken a huge step toward solving this problem, by using an intense laser beam to shift the phase of the electrons themselves.

First, they built a laser beam 100 million times brighter than the surface of the sun. They generated this beam by trapping a laser between highly polished mirrors, which bounce it back and forth 10,000 times to build up intensity. Then, the researchers positioned the laser so that it only interacted with the straight-through electrons, rather than the electrons that collide with the specimen, so both populations would be shifted by the same quarter wavelength. When the populations then recombine, their interference produces a large brightness difference, increasing the contrast between specimen and background.

This enables huge improvements in cryo-electron microscopy. Before, researchers could image only about 10 percent of human proteins in purified form, and under 1 percent of proteins inside intact cells, mostly larger proteins like hemoglobin. The laser phase plate could push those numbers past 50 percent, while improving their resolution too. It means researchers can see which proteins bind to each other inside living cells. They are already studying mutated lysosomes, or the recycling organelles in cells, implicated in Alzheimer’s disease.

The EU will adopt streamlined approval pathways for lightly gene-edited crops. Until now, all gene-edited crops in the EU have been regulated, regardless of how minor the edits were, under the GMO pathway. This regulatory process required many experiments – like feeding the engineered plants to rodents for 90 days to see if they got sick, proving that added proteins could not be allergenic, and mapping out all possible effects the crop could have on the environment – before approval. This process took about five years of work, and cost between 10 to 16 million euros.

But this month, the European Parliament endorsed a new regulatory system where crops carrying gene edits that are modest enough to have arisen through conventional breeding can go through expedited approval pathways. Many other countries have already adopted similar regulatory pathways that distinguish between ‘gene-edited’ and ‘GMO’ plants, including Australia, Argentina, the United States, Japan, and Brazil.

Under the new guidelines, which will go into effect in two years, engineered plants that could have been made through conventional breeding techniques will have an easier path to approval. This new pathway applies to any plants carrying less than ~20 genetic changes and with no foreign, non-plant DNA. These plants won’t need to be labeled as GMO in supermarkets, either.

Many examples of ‘gene-edited’ crops will become easier to approve in Europe as a result, including non-browning mushrooms, which are typically made by knocking out a single gene encoding an enzyme that causes that browning, and are cleared US regulatory review back in 2016. Another example is wheat resistant to powdery mildew, made by knocking out a mildew-susceptibility gene.2

Subscribe now

A synthetic cell that can eat, grow, and divide. For the first time, scientists have made a synthetic cell (called SpudCell) that’s capable of ‘feeding, growth, replication, division and selection [...] entirely using components scientists put there.’ Although SpudCell is definitely a cell, it is not alive, because it can only divide a couple times before expiring.

It is basically a bag of lipids filled with proteins and DNA. Its genome spans 90,000 basepairs of DNA across seven plasmids. Its DNA replication is simple, using a DNA polymerase called Phi29, which floats around, randomly grabs plasmids, and copies them. This happens continuously. Its protein synthesis is more complicated, involving dozens of proteins. And SpudCell cannot make its own ribosomes; researchers must supply them from outside.

Whereas normal cells consume nutrients and convert them into useful molecules, SpudCell feeds by fusing with lipid bubbles called ‘feeder liposomes’, which are filled with ribosomes, using a protein engineered to carry short strings of histidine amino acids. These strings latch onto the feeder liposomes and coax them to merge into SpudCell to bring their ‘food’ inside.

Cell division in SpudCell involves a clever trick of biophysics. It turns out that, if you stud the outside of a lipid membrane with bulky proteins, those proteins will crowd each other and repel the cell membrane, forcing the cell to bend and eventually split. And that’s how SpudCell divides.

The next step will be to engineer SpudCell so it divides dozens of times, reliably. Metabolism is probably the biggest requirement for long-term growth. As SpudCell can’t make its own ribosomes or energy, the researchers currently have to pump in fresh supplies constantly. This is fine, in principle, but SpudCell can’t recycle its broken proteins either. So when the ribosomes wear out and its proteins ‘break,’ they simply sit there and fill up space. It has no way to export its waste, so with each cell division, a larger and larger fraction of the cell’s internal volume becomes packed with junk.

Cover illustration: Escherichia coli.

Print subscribers received the full edition in the first two weeks of June. Most articles in the issue have previously been released online; the remainder of the issue is available on the website today. The issue contains pieces on:

• Why British NIMBYs in the 1600s smashed themselves;

• Why we only discovered plate tectonics around the time we went to the moon;

• How p-hacking is ruining nuclear regulation;

• Why Western countries stopped reclaiming land from the sea;

• What’s really slowing down the AI buildout

• How Europe eliminated fox rabies by dropping vaccines from helicopters;

• Alberta, the only place in the world without rats;

• The most unusual housing development in the world; and

• The prison city that kept Japan peaceful for centuries.

You can get a year of the print magazine for $100 here. New subscribers will receive Issue 24 immediately, plus a new issue every two months after that.

Many people know that the Glorious Revolution was central to Britain’s economic divergence from the rest of Europe. The common story holds that the revolution did this by restraining what the government could do. Ben Southwood and Kara Dimitruk argue the opposite: by creating a form of government controlled by landowners, the British state became far more interventionist, capable of overriding encrusted property rights that prevented farmers from investing in their land, travelers from paying for their roads, and landowners from digging canals and building houses. Like in eighteenth-century Britain, maximizing economic growth today may depend on building a pro-change coalition among rightsholders, rather than on trying to override them.

Subscribe now

Without plate tectonics, we cannot explain mountains, deep sea trenches, earthquakes, or volcanoes. It tells us where to expect oil and why fossilized sea creatures show up in the middle of the desert. Given its extraordinary simplicity, it is surprising how long it took for plate tectonics to become consensus, writes Elizabeth Van Nostrand. People had noticed for centuries that South America and Africa fit together, but most geologists remained dismissive until the second half of the twentieth century. Only in the 1960s, when the US Navy funded research for submarine navigation did the consensus change. Plate tectonics may be the Platonic ideal of a scientific paradigm.

Is it better to drink one beer every evening for a year, or drink 365 beers in one evening? The answer may seem obvious, but the rules governing nuclear power are based on the idea that, when it comes to radiation, both doses are equivalent, explain Alex Chalmers and Ben Southwood. The studies often cited to justify treating any radiation exposure as intolerable turn out to be textbook cases of p-hacking; even the worst nuclear accidents have never had the long-term consequences these studies predict. Low doses of radiation are almost certainly safe, and a regulatory system that reflected that truth would make nuclear power far cheaper to build.

Since 1985, North Korea has reclaimed 14 times more land than the entire United States. America isn’t uniquely bad at this: across the entire Western world, land reclamation halted almost completely in the early 1970s. The timing of this change, argue Zigmund Forrest and Max Tabarrok, suggests that it was modern environmentalism that killed it. Land values have risen enormously in the last fifty years, and reclaiming land is technologically feasible near almost every major American and European city. To build more land, all that needs to happen is for it to become legal again.

The limit on building data centers is the time it takes to get connected to the grid. Replacing the current first-come, first-served system with something closer to an auction and letting data centers plug in immediately if they agree to power down for a few hours a year could unlock far more capacity than building new plants alone, writes Chris Gillett. These changes would be almost free, bring down electricity prices, and dramatically speed up the construction of new data centers across America and much of Europe.

Subscribe now

We commonly vaccinate humans and pets. But more than half of all infectious diseases are zoonotic, and a majority of those originate in wild animals, rather than pets or livestock. Rather than wait for diseases to spread, vaccinating wildlife directly is the cheapest way to protect humans, save species from extinction, and spare animals painful deaths, explains Michelle Ma. For some diseases, we’ve already done it: airdropping vaccine-laced chicken heads over the Swiss Alps and trapping koalas to vaccinate them against potentially fatal chlamydia.

In a world map of rat habitats, only one blank space sits amidst a sea of red: the Canadian province of Alberta. Alberta has been free of rats for more than seventy years, making it a rat-free expanse second in size only to Antarctica, writes Deena Mousa. It did this by preventing them from settling at all: anticipating the corridors through which rats could enter, poisoning their potential habitats, and maintaining a state of permanent vigilance.

In 2002, a Canadian indigenous tribe, the Squamish Nation, managed to recover 11 acres of land in central Vancouver that had been seized from their ancestors in 1913. Freed from the zoning rules that keep the rest of Vancouver low-rise, the Nation voted to maximize density, and are now building eleven towers which will eventually house 9,000 people, writes Anya Martin. The story of the Squamish teaches us two things: when they benefit from development, people will vote for it, and when a development enjoys legitimacy, other parts of government will hesitate to block it.

Between 1600 and 1868, Japan’s ruling family kept the country almost entirely free of war. It did this by forcing its warrior aristocracy to live in a single city, writes Samuel Hughes. At its height, Edo, now Tokyo, was the largest city on Earth. It was less a functioning capital than an extremely effective, extremely expensive prison, sorting samurai, daimyo, and commoners into walled quarters sealed by checkpoints that closed every night. Edo was an enormous drain on taxpayers around Japan; in exchange, the country lived through a quarter millennium of peace.

Notes on Progress

We released a few Notes on Progress since the last issue:

• The miracle of modern epidurals, by Phoebe Arslanagic-Little

• How bacteria solved the mystery of inheritance, by Kevin Blake

• European housing politics should be Americanized, by Samuel Hughes

• Why Spain has the best cities in the world, by Harry Law

• The flattening of American city flags, by Ned Donovan

• What we can learn from a Chinese cure for a brutal blood cancer, by Ruxandra Teslo and Amol Punjabi

• A review of Tyler Goodspeed’s book, Recession, by Mark Koyama

• An architectural review of Washington, DC, by Samuel Hughes

• The education of Ben Southwood, by Ben Southwood

• How daraxonrasib made pancreatic cancer treatable, by Ruxandra Teslo

The Works in Progress podcast

We’ve released podcasts on;

• Local government

• Sculpture

• How nineteenth century cities expanded so quickly and so well.

• The articles in this very issue

This season of the Works in Progress podcast is now over. Keep your eyes peeled and ears pricked for the things to come.

Events

We hosted lightning talks on housing and infrastructure in Berlin; a party to celebrate Issue 24 in Washington, D.C.; and a behind-the-scenes glimpse at the design of the print magazine in New York.

Coming up soon:

• Cambridge, UK: Subscriber-only Issue 25 launch party, Friday 21st August

• Brussels: How can Europe catch up on AI?, Tuesday 8th September

Plus subscriber-only events in San Francisco and London. Sign up to the print magazine to get the details!

What we’ve been up to

• Sam finished up as a judge on the Orwell Prize for Political Writing.

• Saloni has been writing regular round ups of biology breakthroughs with Niko McCarty. She also wrote about why Covid vaccine trials were so fast, and interviewed the inventor of the second malaria vaccine, which is much cheaper and scalable than the first.

• Pieter got into an argument with Paul Krugman and wrote two pieces about how Europe should think about AI.

• Aria was on the Inkhaven podcast talking, yet again, about sexiness.

• Rachel has been obsessively reading the work of Antal Szerb, a Hungarian novelist and literary critic, and translating some of his essays into English.

• Ellen stayed in a capsule hotel in Berlin and spent the heatwave trying to brew the perfect iced tea.

• Ruxandra recently visited Washington, DC to advocate for clinical trial reform and she was very happy to see the recent initiative from the HHS focused on making Phase I trials faster.

Chernobyl was the world’s worst ever nuclear disaster. The reactor was built to a flawed design. In 1986, its operators disabled automated safety systems and removed control rods to perform a late-night test. The coolant water overheated, speeding up the reaction until it flash-boiled into steam and violently shattered all the nuclear fuel in a matter of seconds. The graphite in the reactor then caught fire.

Six hundred workers were present when this occurred. Of these, 134 received high doses of radiation, between 800 and 16,000 millisieverts, mostly within hours. Twenty-eight of these died in the first three months, and another 19 died before 2004, though not all from radiation-related causes. While first responders have shown a slight increase in rates of leukemia, there has been no increase in solid cancers.

When the reactor exploded, it released massive amounts of radioactive material into the atmosphere. This ash settled onto the grazing regions of Ukraine. Dairy cows ate it and secreted it into their milk. Every person who drank this milk ended up with some quantity of radioactive iodine concentrated in their thyroid gland. Since children have smaller thyroids, their effective doses were much larger. The hundreds of thousands of children exposed have been closely screened in the years since, and authorities have identified 6,000 thyroid cancers. Fifteen people have already died of these cancers, and 200 might in the long run. These thyroid cancers were completely avoidable because the iodine has a half-life of eight days. After the Windscale fire released radioactive fallout onto grazing land in 1957, Britain discarded contaminated milk for 44 days, thereby avoiding any harm.

Subscribe now

Chernobyl is the only accident in commercial nuclear history that has exposed people to large enough doses of radiation to poison and kill them. But even it has caused only hundreds of early deaths, despite the exposure of millions of people in the exclusion zone and nearby. Radiation impacts on Scandinavia and Germany, where there were major fears about the effects of the fallout, were nugatory. Evacuations and relocations to avoid small additional background radiation levels may have caused more harm than they averted. The same is true of Fukushima and Three Mile Island, the other two large nuclear disasters, but to an even greater extent: neither saw any responders die of the direct effects of radiation, and neither shows any clear impact on cancer rates.

Two years before Chernobyl, an explosion at a pesticide plant in Bhopal, India, released toxic methyl isocyanate gas that killed at least 2,000 people instantly, permanently disabled another 4,000, and caused 550,000 injuries in total. In 1975, the Banqiao Dam in China failed, flooding 12,000 square kilometers, drowning at least 25,000 people, and destroying perhaps five million houses.

Whereas Chernobyl is a household name, Bhopal and Banqiao are mostly familiar only to specialists. People have much greater familiarity with and concern about the risks created by nuclear power, and the world’s international radiation protection regime is based on the idea that any release of radioactive material from a nuclear power plant is intolerable. This has led to regulations that have increased the costs of nuclear electricity over time to the point where it is widely considered a slow, backward, and ineffective technology.

The idea that any release of radioactive material is an intolerable disaster rests on the claim that radiation is harmful even in small, spread-out doses. But this claim is not well supported. The studies that claim to show harms from slow, drawn-out ionizing radiation are unconvincing. By giving them undeserved credence, we may be foreclosing one of the world’s most powerful technologies.

Trouble in Taipei

Between 1982 and 1984, recycled steel contaminated with cobalt-60 was unknowingly used in the construction of more than 180 buildings in Taiwan, including schools, businesses, and approximately 2,000 apartments. Cobalt-60 emits deeply penetrating gamma radiation, which in high doses is fatal: in 2000, three people died from acute radiation poisoning when a Thai scrap merchant took apart a radiotherapy machine containing large amounts of it. Over two decades, more than 10,000 people occupied these buildings, receiving an average total radiation dose of 400 millisieverts, about seven times more than the average American would receive over the same period from background radiation. This makes the Taiwanese buildings a good test of the claim that chronic background radiation at low daily rates damages human health.

A series of academic papers reconstructed the doses that different affected inhabitants experienced, combining thousands of on-site readings with estimates of their time spent at home. CJ Tung and colleagues built a model in 1998 of 24 of the 1,327 apartments that had then been identified as irradiated, breaking them down into one meter by one meter squares, and using dosimeters to measure radiation in those squares, to get an idea of how residents might have been affected.

Doses varied substantially. Most units received trivially low doses, less than the radiation exposure from one full-body medical CT scan per year (ten millisieverts). A small fraction of units received nearly 1,000 millisieverts per year, equivalent to a hundred CT scans. Later studies that mapped out these doses in more detail found that some sections of rooms were exposed to over 8,000 millisieverts per year, equivalent to about two CT scans every day.

A 2004 preliminary report, followed by a 2006 study (Chen et al), was the first to attempt to measure the health effects in this group. There were no cases of radiation sickness nor any major chromosomal aberrations. Affected Taiwanese had biomarkers of cellular stress nearer the upper end of normal reference ranges, but none linked with observable health effects. Cancer rates were, unexpectedly, dramatically lower than in the population at large.

Chen interpreted this as evidence of the health benefits of radiation. This theory, known as hormesis, holds that low doses of stressors, including ionizing radiation, can improve health (in this case, reducing cancer risk) by triggering the body’s repair systems in much the same way that exercise improves fitness by stressing the cardiovascular system. While popular among a small community of researchers, it has not gained widespread acceptance due to limited and conflicting evidence in humans.

This interpretation of the Taiwan data is dubious because it wasn’t able to control for age. Those affected by the cobalt-60 radiation were far younger than the average Taiwanese. Since younger people are less commonly diagnosed with cancer, this is a very significant limitation. A US Environmental Protection Agency (EPA) review, describing the Taiwanese apartment data alongside some similar cases, warned that ‘studies on these populations are ongoing and suffer from various shortcomings, including incomplete follow-up, dosimetric uncertainties, limited statistical power and confounding’.

Torture the data and it will confess

Later studies fixed most of these problems, linking good estimates of the doses individuals experienced with their health outcomes and adding the missing age data. Contrary to the previous report, the studies generally claimed to find that low doses of ionizing radiation can cause cancer. But drawing this conclusion from them requires an unreasonable manipulation of statistics.

A 2006 study (Hwang et al) in the International Journal of Radiation Biology, for example, found slightly elevated incidences of thyroid cancer in women and leukemia in men across a sample of 7,271 people. But overall cancer rates were still lower in this group than in the general Taiwanese population, even after controlling for age.

The way the researchers found these higher rates of cancer was to break cancer cases down into 77 subtypes, such as tongue cancer in men or kidney cancer in women, and see if any of these had higher rates than expected. This approach has two problems. The first is that when you divide cancer cases into 77 buckets, even small and random variations in one or two of the buckets can create the appearance of a relationship. Every statistically significant site-specific result showing higher cancer incidence relies on seven or fewer observed cases. Across 77 different statistical tests, we would expect to see statistically significant results in four cases purely due to random variation. The second problem is that the authors did not register their hypotheses in advance: we have no idea whether they sliced the data into hundreds of different tests before cherrypicking those that gave them statistically significant correlations.

Share

The biggest issue with drawing the inference that low-level radiation harms human health is that the exposed population actually have lower cancer rates than unexposed people. Just like in Chen et al, the number of total cancer cases observed is substantially lower than expected.

Don’t back down, double down

A 2017 study in the British Journal of Cancer (Hsieh et al) follows up on this result, with ten years more data on whether affected people got ill, again using more accurate dose-rate profiles, more closely associated with particular individuals. Like Hwang et al, they claim their findings show that ‘low-dose-rate radiation exposure increases risks of breast cancer and leukaemia’, but the data is similarly brittle.

Within their sample of around 6,000 exposed Taiwanese apartment dwellers and schoolchildren, female breast cancers were higher at higher levels of exposure: 100 millisieverts of exposure was linked to an 11 percent higher cancer risk. This result is statistically significant. The study finds a few other results that are narrowly significant, but only out of a table of dozens, just like the previous study.

But again, the studies fail to state which tests they planned to do beforehand or that they began the analysis with the hypothesis that leukemia (but excluding multiple myeloma and chronic lymphocytic leukemia) would go up after a delay of two years, whereas rectal, stomach, liver, and thyroid cancer would be unaffected – or that cancers overall would be no higher in the study group than among totally unaffected Taiwanese. If they’d entered their research with this hypothesis, it might make the results more credible. Instead, they appear to have stumbled across a handful of correlations by chance.

And once more, the authors don’t highlight that the irradiated group has significantly lower overall cancer rates than the general Taiwanese population.

While we can comb through the data and infer that the average age of the subjects in Hwang was 33. The samples are slightly different, so we can’t just add ten years to get an average age of 43 for Hsieh. The UN Scientific Committee on the Effects of Atomic Radiation estimated that the average age of the Hsieh sample was about 45, seven years older than Taiwan’s population overall in 2012. By 2012, the irradiated apartment dwellers had experienced 247 cancers, across 97,106 person years. Yet the cancer rate for Taiwan as a whole between 2008 and 2012 was about 390 per 100,000 person years.

Overall, cancer rates seem to be almost 35 percent lower in the affected group. If being irradiated with hundreds of millisieverts per year appears to have no effect, or even reduces cancer rates compared with the general population, this strongly implies that the links these two papers identify between much smaller doses of radiation and particular kinds of cancer are random noise.

Subscribe now

Made aware of this, Hsieh responded (as did Hwang) that these gaps must be down to socioeconomic status. Is this true? The best argument provided is that these were residents of new buildings constructed during an economic boom, suggesting that the apartments were relatively expensive. Though no data on the actual socioeconomic status of their residents exists, we can make some educated guesses.

First, though new, some of the buildings were public housing intended for poorer residents or public employees. This makes it unlikely that their inhabitants were wealthier people projected to have better health outcomes than the rest of the population.

Second, even if it were true that the residents were richer than average, this still wouldn’t account for the decreased cancer rates. Existing data suggest that Taiwanese health differences by socioeconomic status do not close this gap: overall cancer incidence is ten percent lower among doctors than in the general population. The incidence of colorectal cancer, one of the most common cancers, is actually lower (by about 20 percent) at the bottom of the wage ladder in Taiwan, though it is higher among those with the lowest education. None of these variations approach the 35 percent lower rates of cancer seen in the irradiated apartment residents.

This is not to claim that Hsieh’s paper provides strong evidence for the health benefits of radiation, as some fans of nuclear power have suggested. Most likely, these results are evidence of nothing.

The perils of low-dose science

From 2011 onwards, scientists began to realize that significant numbers of famous, eye-catching findings were unreplicable, in what became known as the replication crisis. Starting in psychology – once-popular ideas like power posing or the brain-enhancing effects of classical music began to be debunked – before the same occurred across every discipline.

The Taiwan papers have the classic tell of such findings, using tricks to turn random noise into statistically significant results, a phenomenon known as p-hacking. One such trick is dicing a population up into as many different subgroups as possible, expanding a researcher’s likelihood of finding something by chance.

It is inherently difficult to find out if low doses of radiation affect health. Populations vary hugely in all sorts of health, lifestyle, and genetic factors. The anticipated cancer effects of radiation would be low, even for those who expect to find them. Researchers would need a huge sample size and very carefully designed analysis to have any hope of detecting a signal amid the noise. INWORKS, first published in 2015 and updated in 2023, is the most serious attempt. It looks at cumulative low-dose radiation among 300,000 nuclear workers in France, the US, and Britain, measured by badge dosimeters, and finds that each additional 100 millisieverts of lifetime ionizing radiation exposure is associated with five percent higher cancer mortality rates, adding about one percent to the lifetime risk of dying of cancer (compared to an average of about 34 percent).

Subscribe to print

For comparison, 100 millisieverts is about ten full-body CT scans, whereas the median INWORKS worker experienced a four-millisievert dose. Eating 50 grams of processed meat per day is associated, after controls, with a lifetime colorectal cancer risk 18 percent higher, and smoking with a lung cancer risk 1,500 to 3,000 percent higher.

The INWORKS study is the best single piece of evidence for an effect of cumulative low-dose-rate radiation on health, but the size of the effect is small enough that it is far from a given. For one, the INWORKS study does not attempt to account for background doses, despite the fact that different people will have different levels of background exposure, depending on factors like where they live and how many medical scans they have. The average lifetime background dose in the UK is about 70 millisieverts, similar to that in the US and France, meaning that more than 90 percent of INWORKS subjects got most of their exposure from natural background radiation.

Another problem is that INWORKS’s significant result is driven by subjects between the 75th percentile, meaning lifetime exposure of roughly 20 millisieverts, and the 90th, at roughly 50 millisieverts. The relationship between exposure and cancer is not significant for doses between 0 and 20 millisieverts. Only when expanded to doses between 0 and 50 millisieverts does a significant effect appear, before weakening steadily as higher doses are added in, though not to the point of becoming insignificant.

This sensitivity makes the results fragile and is one reason why many look instead at studies with higher doses. The median INWORKS worker received a dose of four millisieverts, which according to INWORKS’s model, would correspond to increasing the lifetime risk of dying from cancer from the US average rate of 17.2 percent to 17.23 percent. An effect this small is hard to confirm even with 300,000 subjects, given so many unmeasured confounders.

Historically, many people have received doses of thousands or even tens of thousands of millisieverts, similar to those of the Taiwanese apartment dwellers. There are cases of Keralans exposed to sand containing thorium; Manhattan Project scientists who inhaled so much plutonium that they peed it out; early British radiologists who worked without any protection from the X-rays they worked with. These groups suffered long-term health effects only if they absorbed high dose rates.

One of the most horrific and notorious cases of radiation exposure was that of women employed to paint radioactive radium onto watches for glow-in-the-dark dials. Early dial painters were told to lick their paintbrushes for greater precision. Those that did ingested radium at extremely high internal doses and developed necrosis of the jaw and often-lethal bone cancers. But the thousands that did not lick their brushes, despite receiving doses that were often hundreds of times higher than normal, did not see any higher rate of cancer.

Though unlikely, it is possible that future studies will reveal a more substantial correlation. In the meantime, the lack of any strong signal in the Taiwan data is one of many good indicators that low-level radiation is not a cause for concern. Where radiation does harm people is when they are exposed to high, acute levels that even the worst nuclear disasters seldom release. When people are looking this hard, absence of evidence is, in fact, pretty good evidence of absence.

Alex Chalmers is a staff writer at the Cosmos Institute and a former editor at Works in Progress.

Ben Southwood is an editor at Works in Progress.

One of the most expensive projects in history is under construction in Abilene, Texas. This joint venture, Stargate, is the flagship of a bigger project by the same name led by OpenAI and Softbank, and is expected to cost well over $40 billion for a high-performance computing campus that will train new generations of AI models.

Stargate is just one major project in one of the biggest investment booms in history, driven by the belief that increasingly powerful AI models can deliver explosive economic growth. But it will require enormous amounts of electricity to work: Stargate is expected to draw 1.2 gigawatts, as much as 313,000 median American family homes, at peak load. A report by EpochAI and an energy research institute projected that total AI computing power would reach 100 gigawatts worldwide in 2030 if the 2025 growth rate stays steady. And data centers aren’t the only energy-hungry element of the AI revolution. The biggest battery manufacturing plants in the US draw energy at a rate of 115 megawatts, and the first phase of TSMC’s Arizona semiconductor plant will draw 200 megawatts.

The primary bottleneck to this growth is the availability of electricity. But this doesn’t mean there is an energy shortage. Instead, the constraint is connecting the flood of new data centers and the plants to power them to the electric grid. Before any new piece of infrastructure can be connected, grid operators must study how it will change power flows around the grid and determine whether upgrades to the system are required. That process is significantly backlogged. Though the median power plant in 2005 waited less than 20 months for interconnection, this had jumped to 55 months by 2023.

The interconnection process wasn’t created for today’s world. Grids use an inflexible first-come, first-served queue that leaves some of the most valuable projects stuck behind less important ones. They also evaluate according to rigid conditions that don’t reward plants for being willing to cover their own power needs for short periods. To prepare for the AI age, grid processes need to change.

A power-hungry future

Estimates vary for how much power will be needed by the data centers and chip manufacturers of the future, but the heads of every major AI company agree that they will need more than they are currently able to get. Jensen Huang, CEO of Nvidia, has said that ‘every data center in the future will be power-limited’. Mark Zuckerberg said Meta ‘would build … bigger [AI training] clusters … if we could get the energy to do it’. And OpenAI CEO Sam Altman told Congress that ‘the abundance of [AI] will be limited by the abundance of energy’.

Regardless of how the data center boom plays out, there is a long-term shift towards electrification across the economy. Electricity can be converted into work instantly, unlike fuels, and with little energy loss. Electricity creates motion directly, while fuels must first be combusted in an engine. This is why electric vehicles can cost half as much to fuel even though electricity is more expensive than gasoline. The simplicity of electric motors also means that electric vehicles have half the lifetime maintenance costs of gas-powered ones.

Electricity also transmits information. Transistors switch on or off depending on the voltage applied to their gates, which allows circuits to perform logical operations. Radios, screens, and computers cannot run on gasoline alone.

Between 1990 and 2024, the price of electric motors declined by 97.5 percent. Power electronics fell 99.5 percent in price, processors built into devices by nearly 99.9 percent, and batteries 98.8 percent. As prices have declined, performance has improved. For example, the amount of energy a battery can store per kilogram has increased five-fold over the same period.

These trends allowed the progression from the Walkman to the iPod and then the iPhone, as well as enabling battery-powered cars, delivery vans, and bicycles. At the same time, the increased computing power built into devices is giving autonomy to newly electrified cars and trucks, robotic vacuum cleaners and mowers, and drones. The commercialization of humanoid robots may also be on the horizon. The future will be largely defined by technologies that run on electricity.

The grid bottleneck

This growth in demand is already straining power grids. Operators are increasingly forced to use expensive local plants because of what grid operators call congestion: cheaper plants are on the other side of transmission bottlenecks and there aren’t enough cables to get the electricity through. In the United States, the additional costs incurred because of grid inefficiencies like congestion ran to $11.5 billion in 2023, an increase of 45 percent from the year before.

ERCOT, the grid that provides 90 percent of Texas’s electricity (including for the plant being built in Abilene), forecasts that it won’t have enough power to meet demand in summer 2028. PJM is the US’s largest grid, both by the amount of electricity it provides and the population in its coverage area, serving an area between Chicago, New Jersey and North Carolina. In 2025, PJM was not able to buy enough future generating capacity to meet projected demand. MISO, another large US grid operating between Louisiana and Minnesota, concluded in one study that ‘resource adequacy risks could grow… absent increased new capacity additions’. PJM’s CEO put it more plainly: ‘We need capacity – a lot of capacity.’

Discussions about expanding electricity supply to power the future often become debates about which source is most suitable: gas, nuclear, solar, or something else. But these are a distraction. Far more fundamental is ensuring power can be efficiently delivered where needed.

When different generation technologies coexist, they can average out to a grid that is cheaper, more reliable, and less polluting than any single type alone. The question isn’t which technology to use, but what balance. But this question isn’t best answered in the marketplace of ideas. Instead, it should be addressed in the marketplace for electricity.

The market for electricity

In the US and Europe, power grids are largely liberalized: provided they can get the necessary permits, independent developers build power plants, and the local utility is required to connect those plants to the grid. In the United States, 88 percent of large-scale power projects currently in development are privately organized and funded.

The power market is run by the grid operator’s economic dispatch software. Each power plant tells the operator its costs, and the operator commissions the cheapest plants, accounting for transmission constraints. As load increases during the day, the operator keeps commissioning the next cheapest plant. The price of power is set at the marginal cost of the next cheapest plant, and that’s the price every power plant is paid.

Market prices signal to power plant developers about levels of supply and demand. In the same way, prices balance different energy sources based on the strengths and weaknesses of each. For instance, as more solar panels are built, the value (and therefore price) of power during the middle of the day, when the sun is shining most, adjusts downward. From December 2020 to September 2025, maximum solar output in ERCOT increased from 4 to 29.8 gigawatts. And from 2020 to 2025, the value of power at 1pm relative to the highest-priced hour decreased from 92.9 percent to 38.7 percent. As one technology type becomes overbuilt, prices reflect that and developers react accordingly.

The evolving daily price shape in response to the abundance of solar energy was a signal that the grid needed storage capacity, and power plant developers responded. From 2020 to October 2025, ERCOT went from having almost no battery storage to a combined battery discharge of 8.6 gigawatts. The same process has played out in California and many European markets.

One might assume that the price of electricity for consumers is dictated by market forces, like those that regulate supply and demand across different power plants. But to a large extent, it is not. Grid infrastructure, like large power lines, is generally planned by the grid operator, and the cost is passed on to consumers at a price approved by state and federal regulators. In one typical utility territory within ERCOT, the portion of regulated costs on the average residential customer’s bill has grown from 28 percent in 2002 to 40 percent in 2025.

Regulators of all major grids have set caps on wholesale prices in response to public outrage at price volatility. As a result, the generators needed to keep the grid reliable are sometimes unprofitable. Under normal market circumstances, generators would stop running when it wasn’t profitable to do so. Instead, regulators put further policies in place to prevent this. Markets for capacity mean that generators are paid not for energy itself but for committing to be available if there is extra demand. Must-run agreements pay unprofitable generators to keep running if they keep the grid reliable. These are negotiated bilaterally between generators and the grid operator, outside of any wider competitive process.

Policy choices also shift the equilibrium. For example, America’s Inflation Reduction Act gives a $30 tax credit for every megawatt-hour produced by qualifying renewables. Power plants that opt in, typically wind, paradoxically often offer their power at negative prices, making money from the tax credit even when they literally pay consumers to use them. At times, a large enough share of the market offers electricity at a negative price that electricity overall (not just from one supplier) can have a negative price. A similar dynamic is playing out in some European countries.

Despite these interventions, which make them less efficient, markets still find an equilibrium. The interaction of supply and demand creates prices that power plant developers use as indicators for what the market does or doesn’t need more of. If prices are high, new power plants enter. That’s why arguing about the best power generation method is overrated. Well-designed energy markets answer this question automatically. The real bottleneck is connecting to the grid at all.

Share

Power struggles

xAI’s Memphis data center operated partially off-grid for months. When it first came online in 2024, it could reportedly draw only eight megawatts from the grid (enough to power a few thousand electric toasters). Rather than wait for its grid connection to be upgraded, xAI installed 422 megawatts of on-site gas turbines. Once transmission upgrades were completed, the project would shift to consuming grid power and the on-site generators would be used only for emergency backup.

Such off-grid generation is a temporary solution. Grid power is more reliable and, on average, cheaper. But thanks to the long queue of projects waiting for connection, 62 percent of data centers are considering off-grid solutions, either to get up and running faster or to improve reliability. Google is even exploring the possibility of a data center in space powered by solar panels. Grids connect to new generators and energy-hungry infrastructure only after studying how to do so using an engineering model that simulates power flows during peak load scenarios. If the new infrastructure would cause overloads on any parts of the system, then those elements need to be upgraded. The utility then needs to estimate the cost of those upgrades and build them.

The grid operators who run these studies are typically public bodies charging a small fee on electricity sales to fund their operations without seeking to make a profit. State utility commissions and the Federal Energy Regulatory Commission have determined that grid operators should run the interconnection queue as a first-come, first-served process that is essentially free.

That process is moving very slowly, creating a huge backlog of mostly phantom projects. Every US grid has more power plant capacity waiting to be connected than there are gigawatts of peak demand. The backlog also exists for the separate but similar queue of infrastructure not yet connected to the grid. Across ERCOT, there were 143.5 gigawatts of data centers seeking to connect as of October 2025. This compares to ERCOT’s highest ever total demand of 85.9 gigawatts in August 2024.

This system was designed for a different era. The last time electricity use grew five percent annually or faster was between the 1950s and 1970s, during the adoption of air conditioning, refrigerators, dishwashers, and washing machines. From 2005 to 2023, electricity use was almost completely flat. But as that lull in growth comes to an end, the grid will have to adapt.

Crossed wires

The main flaw of the interconnection process is that it uses a first-come, first-served queue. This means that high-priority requests can spend years stuck at the back of the line behind other less important ones.

Some requests are speculative, submitted by developers before they have ready customers. Some are duplicative, meaning a developer fishing for a good spot has requested to interconnect the same project in multiple locations. These are among the reasons that 72 percent of requests to connect submitted since 2000 were ultimately withdrawn. Other requests are high quality but small and low value. This creates a feedback loop: the harder it is for developers to estimate the cost to interconnect, and the longer they have to wait for an answer, the more speculative requests are made, further clogging the system.

Every major grid has a roughly similar process. The system impact study comes first. The operator models the grid during peak demand conditions and assesses the cost of any necessary upgrades. After reviewing those costs, the interconnection customer (the developers of the power plant or power-hungry infrastructure) decides whether to proceed. Almost 40 percent of withdrawals between 2020 and 2023 were at this stage. If the customer proceeds, the grid operator then determines how to physically connect the project to the grid. Again, it delivers a quote for these costs to the customer, who then decides if they want to proceed. If so, they sign an interconnection agreement, and the utility begins work on the upgrades.

There are some opportunities to automate these workflows, but each request takes time. The median delay from initial request to the interconnection agreement was 34.2 months for agreements signed in 2023.

Another major issue is restudies. Once a system impact study identifies required network upgrades, those upgrades are added to the grid model that’s used to study subsequent projects in the queue. If those upgrades are not built because the earlier project withdraws, any subsequent studies may need to be redone. In one extreme case, a restudy increased a 242-megawatt wind project’s network upgrade costs from $33.5 million to $99 million after the project was already operating.

The slowness of the interconnection queue adds to households’ energy costs. The clearest example of this is found in PJM, which has the slowest queue of the US grids. In 2025, PJM’s electricity suppliers paid $14.7 billion at auction to make sure they’d have enough power to supply their customers, a huge jump from $2.2 billion the year before. Meanwhile, many gigawatts of renewable power projects have been sitting in the queue for five years or more. If just 30 percent of those projects had been interconnected, the auction’s cost would have been 63 percent lower.

Grids have adopted many sensible reforms to the interconnection queue, such as requiring higher deposits to enter the queue and forcing developers to prove they have land to build on and to disclose if they’re making duplicative requests. The most significant reform has been transitioning to cluster studies, which study multiple projects in the same simulation. This reduces restudies because removing any one project has less impact on the overall solution. Clusters also allocate costs more fairly. This prevents a single project triggering a major transmission upgrade that renders it uneconomical. In cluster studies, the cost of these backbone upgrades are shared among all the projects that would benefit from them. While these were necessary reforms, the backlog has only grown as they fail to address the fundamental irrationality of the interconnection process itself: the inflexible first-come, first-served queue.

Tragedy of the commons

In the early 2000s, regulators wanted to level the playing field between new independent producers and incumbents. They worried that utilities might preference their own projects. As there was plenty of spare capacity at the time, the first-come, first-served system seemed both simple and fair.

But today, transmission capacity is a limited resource and independent power producers are thriving. This means there is much less concern around the power of traditional utilities. In response, many grids are proposing mechanisms to allow more valuable projects to jump the queue. MISO, PJM, and SPP, three large grids in the US, have proposed mechanisms to prioritize projects that are most viable or most necessary for the system’s reliability. But these mechanisms are band-aid solutions.

The flood of requests is a typical ‘tragedy of the commons’. Everyone is incentivized to spam the queue with requests. Auctions can fix this.

In the fishing industry, when tradable fishing quotas were introduced worldwide in the 1970s, what had been a mad dash for fish became an orderly and efficient process. Before the quotas, the whole season’s supply was caught in a few days of dangerous, non-stop fishing. Market share went to whoever bagged the fish fastest. Once quotas were introduced, fishers could time their catches with market demand instead of catching everything at the start of the season and then freezing it. And since more efficient fishermen made more money, they were willing to pay more, and quotas went to them rather than the fastest fishers, lowering prices for consumers.

Auctioning new grid capacity could bring similar benefits. The scramble for interconnection would be replaced with an orderly process in which the highest quality projects would get priority. Developers’ bids would reflect both the likelihood that the project will come online and the projected value of the project to the grid if so. Less viable and less valuable projects would be weeded out.

The simplest way to implement an auction would be to create small ‘fast-track clusters’ that receive expedited studies throughout the year. Projects in the regular annual cluster could bid to enter the fast track, and the highest bidders up to some preset number would be admitted. The fast-track proposals recently adopted by some grid operators follow this structure, except that admittance to the fast-track cluster is based on an administrative scoring mechanism, not developer bids. But administrative scoring mechanisms could never capture the subtleties that a developer’s bid would. For example, developers have private knowledge about a project’s chances to get permitted, like whether the site has trees with endangered bird nests or unhappy neighbors generating pushback.

Only connect

Another inefficiency of the current transmission system is that it’s built for peak load conditions that occur only a few hours per year. The rest of the time, much of the grid’s generation and transmission capacity is sitting idle. In 2024, 42 percent of ERCOT’s capacity went unused for half the time.

Building the network upgrades that allow for this very high peak capacity can take years. But new power plants must wait for that construction to be completed before they can join the grid, even though the equipment being constructed will rarely be necessary. A survey of power developers found that transmission construction was the top cause of project delays.

The solution is to let the power plant come online before the upgrades are constructed on the condition that it agrees to turn off during peaks. The power plant doesn’t contribute to the reliability of the system since it won’t be available when the system is under stress. But it will produce electricity the rest of the time, which will lower costs. This is known as energy-only service.

ERCOT has made this energy-only service, also known as non-firm transmission because it implies no guaranteed ability to export or import power, their default. They call it connect and manage. That’s a large part of why projects move through ERCOT’s queue faster than any other grid operator.

But despite being an option in all organized US grids, 87 percent of interconnection requests by capacity opt for the slower firm transmission service. That’s because non-firm service disqualifies power plants from the payments they could otherwise receive in exchange for being available at times of high demand. Other grids could adopt connect-and-manage if they eliminated this payment system and, like ERCOT, raised price caps to allow energy prices themselves to reflect scarcity value. Short of that, they could make non-firm service more popular by allowing generators to apply for firm service after being interconnected on a non-firm basis.

Subscribe now

Can’t we just use less energy?

These proposed reforms would allow fast interconnection of new power plants. But if AI is a race with national security implications, they won’t be fast enough.

The fastest way to increase capacity for new large loads would be to decrease demand from existing sources. Demand reduction is the option energy planners have always reached for in a pinch. The concept of energy conservation originated in the late 1960s as the US power grid faced resource constraints for the first time in its history. Energy conservation became a national imperative. For the first time, utilities began promoting things like turning off lights and using less air conditioning. Christmas lights were framed as being wasteful and unpatriotic, and in 1973 the National Christmas Tree had only a single light.

Yet while short-term crunches can be fought with conservation, they are difficult to sustain, and increased energy efficiency can simply lead people to using more energy for other purposes. What’s more, the vast majority of electricity users are completely indifferent to the real-time cost to produce electricity, because they’re on fixed rates for terms of months or years. The wholesale cost of a clothes dryer load, which could consume four kilowatt-hours, could range from negative $0.12 to $20, but the retail customer always pays $0.64 at the average US residential rate of $0.16 per kilowatt-hour. This creates irrational behavior, like someone starting a load of laundry while the grid teeters on the edge of a brownout. If customers faced prices more closely linked to real-time costs, they would adjust their energy use accordingly. Prices would be more stable and, on average, lower.

Already, we’ve seen that power costs change throughout the day because of the increasing availability of solar power. Some power suppliers offer time-of-use rates that charge a different rate at each hour of the day to reflect what it costs to provide. As these are adopted more widely, the highs and lows of demand will increasingly follow the same daily pattern as wind and solar availability. Few customers think about their bill enough for small price differences to influence their behavior, but their power-hungriest devices, like their thermostat or EV charger, could schedule themselves to automatically run when the cost is lower.

Daily reconfiguration could be helpful. More helpful would be reducing demand during the few hours per year with extremely high wholesale costs, when the grid is under greatest stress. Even without time-of-use rates, customers can give their utility provider control of their most power-hungry devices, and the utility can turn them down during grid emergencies in exchange for a reimbursement on their bills. The US had 30.5 gigawatts of this capacity, called demand response, in 2022. But the headroom this gives is unreliable because participants may override the utility’s control, turning their air conditioning back up if they are too hot, for instance.

That’s what makes batteries, installed at customers’ homes, the ultimate load-managing tool. Electronic devices continue to work as normal in periods of high demand, just switching from grid to battery power. And batteries offset the demand of the entire home, not just one or two devices. Combined with rooftop solar, they can significantly reduce a home’s reliance on the grid, making room for new large loads. Perhaps the greatest advantage of all is that these at-home power resources don’t have to go through the interconnection queue; the installation process takes weeks to months, not years.

But devices like this free up relatively little grid capacity compared to the huge amounts that will be needed to power the AI revolution. They’re also relatively expensive, as the cost of installation has to be repeated on every home individually. Matching the demand of a single two-gigawatt data center, which could be handled by a handful of utility-scale projects, would require installing solar and battery systems at nearly 175,000 households.

The data center trilemma

Most data centers have on-site generators as backup power for if the grid goes down because they need a stronger guarantee of reliability than the grid alone can provide. But this capacity could have another significant benefit.

Like generators, power-hungry infrastructure could come online on a connect-and-manage basis, interconnecting before all transmission upgrades are complete on the condition that it disconnects from the grid during peaks. Instead of turning off entirely, it would switch to their on-site backup power. And just like connect-and-manage lowers grid costs, flexible data centers would also lower costs for consumers by ensuring less capacity sits idle outside of peak usage.

Because grid peaks are brief and infrequent, data centers would have to disconnect for only a few hours per year. One study found that 76 gigawatts’ worth of new loads could be added (across an area covering most of the US) if these new loads were willing to disconnect during just 22 hours per year. And those 22 hours of disconnection aren’t consecutive. Each disconnection would last a few hours at most, meaning that data centers could rely on batteries rather than thermal generation. The National Renewal Energy Laboratory estimates that grid-scale, four-hour batteries can be built for $1,300 per kilowatt, as compared to around $2,500 for combined cycle gas turbines.

Disconnecting from the grid isn’t exactly ideal, but given the constraints, developers face a trilemma: data centers can be large, they can come online quickly, or they can receive firm grid service, but not all three. If large data centers want to come online quickly, they’ll have to be flexible.

The powerful shall inherit

The data center boom has exposed the weakness of Western grids. But these are not the only new source of demand for electricity that we can expect in the coming years. Industrial electrification, hydrogen production, water desalination, heat pumps and air conditioning to cope with climate change, electric vehicles, and perhaps even electric aircraft are all likely to increase demand.

The twenty-first century will belong to those who make the most of these developing technologies. Without sufficient power, this will be impossible. And the main constraint to supplying power-hungry infrastructure is not power generation – it is getting that power where it is needed.

This is a blessing: insufficient power would be a much harder problem to solve. Instead, the solutions are simple. The queue of infrastructure that needs to connect to the grid should become more flexible, allowing fast-track slots to be auctioned so that the most valuable and viable projects can start sooner. And payment systems should reward both producers and large-scale consumers that are willing to disconnect for a few hours per year when demand is highest. These simple fixes can give America a power grid fit for the future.

Chris Gillett is a market analyst in electric power. His views don’t represent his employer.