MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here.

MDMA, sometimes called Molly or ecstasy, has been banned in the United States for more than three decades. Now this potent mind-altering drug is poised to become a badly needed therapy for PTSD.

On June 4, the Food and Drug Administration’s advisory committee will meet to discuss the risks and benefits of MDMA therapy. If the committee votes in favor of the drug, it could be approved to treat PTSD this summer. The approval would represent a momentous achievement for proponents of mind-altering drugs, who have been working toward this goal for decades. And it could help pave the way for FDA approval of other illicit drugs like psilocybin. But the details surrounding how these compounds will make the transition from illicit substances to legitimate therapies are still foggy. 

Here’s what to know ahead of the upcoming hearing. 

What’s the argument for legitimizing MDMA? 

Studies suggest the compound can help treat mental-health disorders like PTSD and depression. Lykos, the company that has been developing MDMA as a therapy, looked at efficacy in two clinical trials that included about 200 people with PTSD. Researchers randomly assigned participants to receive psychotherapy with or without MDMA. The group that received MDMA-assisted therapy had a greater reduction in PTSD symptoms. They were also more likely to respond to treatment, to meet the criteria for PTSD remission, and to lose their diagnosis of PTSD.

But some experts question the validity of the results. With substances like MDMA, study participants almost always know whether they’ve received the drug or a placebo. That can skew the results, especially when the participants and therapists strongly believe a drug is going to help. The Institute for Clinical and Economic Review (ICER), a nonprofit research organization that evaluates the clinical and economic value of drugs, recently rated the evidence for MDMA-assisted therapy as “insufficient.”

In briefing documents published ahead of the June 4 meeting, FDA officials write that the question of approving MDMA “presents a number of complex review issues.”

The ICER report also referenced allegations of misconduct and ethical violations. Lykos (formerly the Multidisciplinary Association for Psychedelic Studies Public Benefit Corporation) acknowledges that ethical violations occurred in one particularly high-profile case. But in a rebuttal to the ICER report, more than 70 researchers involved in the trials wrote that “a number of assertions in the ICER report represent hearsay, and should be weighted accordingly.” Lykos did not respond to an interview request.

At the meeting on the 4th, the FDA has asked experts to discuss whether Lykos has demonstrated that MDMA is effective, whether the drug’s effect lasts, and what role psychotherapy plays. The committee will also discuss safety, including the drug’s potential for abuse and the risk posed by the impairment MDMA causes. 

What’s stopping people from using this therapy?

MDMA is illegal. In 1985, the Drug Enforcement Agency grew concerned about growing street use of the drug and added it to its list of Schedule 1 substances—those with a high abuse potential and no accepted medical use. 

MDMA boosts the brain’s production of feel-good neurotransmitters, causing a burst of euphoria and good will toward others. But the drug can also cause high blood pressure, memory problems, anxiety, irritability, and confusion. And repeated use can cause lasting changes in the brain. 

If the FDA approves MDMA therapy, when will people be able to access it?

That has yet to be determined. It could take months for the DEA to reclassify the drug. After that, it’s up to individual states. 

Lykos applied for approval of MDMA-assisted therapy, not just the compound itself. In the clinical trials, MDMA administration happened in the presence of licensed therapists, who then helped patients process their emotions during therapy sessions that lasted for hours.

But regulating therapy isn’t part of the FDA’s purview. The FDA approves drugs; it doesn’t oversee how they’re administered. “The agency has been clear with us,” says Kabir Nath, CEO of Compass Pathways, the company working to bring psilocybin to market. “They don’t want to regulate psychotherapy, because they see that as the practice of medicine, and that’s not their job.” 

However, for drugs that carry a risk of serious side effects, the FDA can add a risk evaluation and mitigation strategy to its approval. For MDMA that might include mandating that the health-care professionals who administer the medication have certain certifications or specialized training, or requiring that the drug be dispensed only in licensed facilities. 

For example, Spravato, a nasal spray approved in 2019 for depression that works much like ketamine, is available only at a limited number of health-care facilities and must be taken under the observation of a health-care provider. Having safeguards in place for MDMA makes sense, at least at the outset, says Matt Lamkin, an associate professor at the University of Tulsa College of Law who has been following the field closely.: “Given the history, I think it would only take a couple of high-profile bad incidents to potentially set things back.”

What mind-altering drug is next in line for FDA approval?

Psilocybin, a.k.a. the active ingredient in magic mushrooms. This summer Compass Pathways will release the first results from one of its phase 3 trials of psilocybin to treat depression. Results from the other trial will come in the middle of 2025, which—if all goes well—puts the company on track to file for approval in the fall or winter of next year. With the FDA review and the DEA rescheduling, “it’s still kind of two to three years out,” Nath says.

Some states are moving ahead without formal approval. Oregon voters made psilocybin legal in 2020, and the drug is now accessible there at about 20 licensed centers for supervised use. “It’s an adult use program that has a therapeutic element,” says Ismail Ali, director of policy and advocacy at the Multidisciplinary Association for Psychedelic Studies (MAPS).

Colorado voted to legalize psilocybin and some other plant-based psychedelics in 2022, and the state is now working to develop a framework to guide the licensing of facilitators to administer these drugs for therapeutic purposes. More states could follow. 

So would FDA approval of these compounds open the door to legal recreational use of psychedelics?

Maybe. The DEA can still prosecute physicians if they’re prescribing drugs outside of their medically accepted uses. But Lamkin does see the lines between recreational use and medical use getting blurry. “What we’re seeing is that the therapeutic uses have recreational side effects and the recreation has therapeutic side effects,” he says. “I’m interested to see how long they can keep the genie in the bottle.”

What’s the status of MDMA therapies elsewhere in the world? 

Last summer, Australia became the first country to approve MDMA and psilocybin as medicines to treat psychiatric disorders, but the therapies are not yet widely available. The first clinic opened just a few months ago. The US is poised to become the second country if the FDA greenlights Lykos’s application. Health Canada told the CBC it is watching the FDA’s review of MDMA “with interest.” Europe is lagging a bit behind, but there are some signs of movement. In April, the European Medicines Agency convened a workshop to bring together a variety of stakeholders to discuss a regulatory framework for psychedelics.

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here. 

Here in the US, bird flu has now infected cows in nine states, millions of chickens, and—as of last week—a second dairy worker. There’s no indication that the virus has acquired the mutations it would need to jump between humans, but the possibility of another pandemic has health officials on high alert. Last week, they said they are working to get 4.8 million doses of H5N1 bird flu vaccine packaged into vials as a precautionary measure. 

The good news is that we’re far more prepared for a bird flu outbreak than we were for covid. We know so much more about influenza than we did about coronaviruses. And we already have hundreds of thousands of doses of a bird flu vaccine sitting in the nation’s stockpile.

The bad news is we would need more than 600 million doses to cover everyone in the US, at two shots per person. And the process we typically use to produce flu vaccines takes months and relies on massive quantities of chicken eggs. Yes, chickens. One of the birds that’s susceptible to avian flu. (Talk about putting all our eggs in one basket. #sorrynotsorry)

This week in The Checkup, let’s look at why we still use a cumbersome, 80-year-old vaccine production process to make flu vaccines—and how we can speed it up.

The idea to grow flu virus in fertilized chicken eggs originated with Frank Macfarlane Burnet, an Australian virologist. In 1936, he discovered that if he bored a tiny hole in the shell of a chicken egg and injected flu virus between the shell and the inner membrane, he could get the virus to replicate.  

Even now, we still grow flu virus in much the same way. “I think a lot of it has to do with the infrastructure that’s already there,” says Scott Hensley, an immunologist at the University of Pennsylvania’s Perelman School of Medicine. It’s difficult for companies to pivot. 

The process works like this: Health officials provide vaccine manufacturers with a candidate vaccine virus that matches circulating flu strains. That virus is injected into fertilized chicken eggs, where it replicates for several days. The virus is then harvested, killed (for most use cases), purified, and packaged. 

Making flu vaccine in eggs has a couple of major drawbacks. For a start, the virus doesn’t always grow well in eggs. So the first step in vaccine development is creating a virus that does. That happens through an adaptation process that can take weeks or even months. This process is particularly tricky for bird flu: Viruses like H5N1 are deadly to birds, so the virus might end up killing the embryo before the egg can produce much virus. To avoid this, scientists have to develop a weakened version of the virus by combining genes from the bird flu virus with genes typically used to produce seasonal flu virus vaccines. 

And then there’s the problem of securing enough chickens and eggs. Right now, many egg-based production lines are focused on producing vaccines for seasonal flu. They could switch over to bird flu, but “we don’t have the capacity to do both,” Amesh Adalja, an infectious disease specialist at Johns Hopkins University, told KFF Health News. The US government is so worried about its egg supply that it keeps secret, heavily guarded flocks of chickens peppered throughout the country. 

Most of the flu virus used in vaccines is grown in eggs, but there are alternatives. The seasonal flu vaccine Flucelvax, produced by CSL Seqirus, is grown in a cell line derived in the 1950s from the kidney of a cocker spaniel. The virus used in the seasonal flu vaccine FluBlok, made by Protein Sciences, isn’t grown; it’s synthesized. Scientists engineer an insect virus to carry the gene for hemagglutinin, a key component of the flu virus that triggers the human immune system to create antibodies against it. That engineered virus turns insect cells into tiny hemagglutinin production plants.   

And then we have mRNA vaccines, which wouldn’t require vaccine manufacturers to grow any virus at all. There aren’t yet any approved mRNA vaccines for influenza, but many companies are fervently working on them, including Pfizer, Moderna, Sanofi, and GSK. “With the covid vaccines and the infrastructure that’s been built for covid, we now have the capacity to ramp up production of mRNA vaccines very quickly,” says Hensley. This week, the Financial Times reported that the US government will soon close a deal with Moderna to provide tens of millions of dollars to fund a large clinical trial of a bird flu vaccine the company is developing.

There are hints that egg-free vaccines might work better than egg-based vaccines. A CDC study published in January showed that people who received Flucelvax or FluBlok had more robust antibody responses than those who received egg-based flu vaccines. That may be because viruses grown in eggs sometimes acquire mutations that help them grow better in eggs. Those mutations can change the virus so much that the immune response generated by the vaccine doesn’t work as well against the actual flu virus that’s circulating in the population. 

Hensley and his colleagues are developing an mRNA vaccine against bird flu. So far they’ve only tested it in animals, but the shot performed well, he claims. “All of our preclinical studies in animals show that these vaccines elicit a much stronger antibody response compared with conventional flu vaccines.”

No one can predict when we might need a pandemic flu vaccine. But just because bird flu hasn’t made the jump to a pandemic doesn’t mean it won’t. “The cattle situation makes me worried,” Hensley says. Humans are in constant contact with cows, he explains. While there have only been a couple of human cases so far, “the fear is that some of those exposures will spark a fire.” Let’s make sure we can extinguish it quickly. 

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Read more from MIT Technology Review’s archive

In a previous issue of The Checkup, Jessica Hamzelou explained what it would take for bird flu to jump to humans. And last month, after bird flu began circulating in cows, I posted an update that looked at strategies to protect people and animals.

I don’t have to tell you that mRNA vaccines are a big deal. In 2021, MIT Technology Review highlighted them as one of the year’s 10 breakthrough technologies. Antonio Regalado explored their massive potential to transform medicine. Jessica Hamzelou wrote about the other diseases researchers are hoping to tackle. I followed up with a story after two mRNA researchers won a Nobel Prize. And earlier this year I wrote about a new kind of mRNA vaccine that’s self-amplifying, meaning it not only works at lower doses, but also sticks around for longer in the body. 

From around the web

Researchers installed a literal window into the brain, allowing for ultrasound imaging that they hope will be a step toward less invasive brain-computer interfaces. (Stat) 

People who carry antibodies against the common viruses used to deliver gene therapies can mount a dangerous immune response if they’re re-exposed. That means many people are ineligible for these therapies and others can’t get a second dose. Now researchers are hunting for a solution. (Nature)

More good news about Ozempic. A new study shows that the drug can cut the risk of kidney complications, including death in people with diabetes and chronic kidney disease. (NYT)

Microplastics are everywhere. Including testicles. (Scientific American)

Must read: This story, the second in series on the denial of reproductive autonomy for people with sickle-cell disease, examines how the US medical system undermines a woman’s right to choose. (Stat)

MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here.

Thanks to the boom in artificial intelligence, the world of chips is on the cusp of a huge tidal shift. There is heightened demand for chips that can train AI models faster and ping them from devices like smartphones and satellites, enabling us to use these models without disclosing private data. Governments, tech giants, and startups alike are racing to carve out their slices of the growing semiconductor pie. 

Here are four trends to look for in the year ahead that will define what the chips of the future will look like, who will make them, and which new technologies they’ll unlock.

CHIPS Acts around the world

On the outskirts of Phoenix, two of the world’s largest chip manufacturers, TSMC and Intel, are racing to construct campuses in the desert that they hope will become the seats of American chipmaking prowess. One thing the efforts have in common is their funding: in March, President Joe Biden announced $8.5 billion in direct federal funds and $11 billion in loans for Intel’s expansions around the country. Weeks later, another $6.6 billion was announced for TSMC. 

The awards are just a portion of the US subsidies pouring into the chips industry via the $280 billion CHIPS and Science Act signed in 2022. The money means that any company with a foot in the semiconductor ecosystem is analyzing how to restructure its supply chains to benefit from the cash. While much of the money aims to boost American chip manufacturing, there’s room for other players to apply, from equipment makers to niche materials startups.

But the US is not the only country trying to onshore some of the chipmaking supply chain. Japan is spending $13 billion on its own equivalent to the CHIPS Act, Europe will be spending more than $47 billion, and earlier this year India announced a $15 billion effort to build local chip plants. The roots of this trend go all the way back to 2014, says Chris Miller, a professor at Tufts University and author of Chip War: The Fight for the World’s Most Critical Technology. That’s when China started offering massive subsidies to its chipmakers. 

“This created a dynamic in which other governments concluded they had no choice but to offer incentives or see firms shift manufacturing to China,” he says. That threat, coupled with the surge in AI, has led Western governments to fund alternatives. In the next year, this might have a snowball effect, with even more countries starting their own programs for fear of being left behind.

The money is unlikely to lead to brand-new chip competitors or fundamentally restructure who the biggest chip players are, Miller says. Instead, it will mostly incentivize dominant players like TSMC to establish roots in multiple countries. But funding alone won’t be enough to do that quickly—TSMC’s effort to build plants in Arizona has been mired in missed deadlines and labor disputes, and Intel has similarly failed to meet its promised deadlines. And it’s unclear whether, whenever the plants do come online, their equipment and labor force will be capable of the same level of advanced chipmaking that the companies maintain abroad.

“The supply chain will only shift slowly, over years and decades,” Miller says. “But it is shifting.”

More AI on the edge

Currently, most of our interactions with AI models like ChatGPT are done via the cloud. That means that when you ask GPT to pick out an outfit (or to be your boyfriend), your request pings OpenAI’s servers, prompting the model housed there to process it and draw conclusions (known as “inference”) before a response is sent back to you. Relying on the cloud has some drawbacks: it requires internet access, for one, and it also means some of your data is shared with the model maker.  

That’s why there’s been a lot of interest and investment in edge computing for AI, where the process of pinging the AI model happens directly on your device, like a laptop or smartphone. With the industry increasingly working toward a future in which AI models know a lot about us (Sam Altman described his killer AI app to me as one that knows “absolutely everything about my whole life, every email, every conversation I’ve ever had”), there’s a demand for faster “edge” chips that can run models without sharing private data. These chips face different constraints from the ones in data centers: they typically have to be smaller, cheaper, and more energy efficient. 

The US Department of Defense is funding a lot of research into fast, private edge computing. In March, its research wing, the Defense Advanced Research Projects Agency (DARPA), announced a partnership with chipmaker EnCharge AI to create an ultra-powerful edge computing chip used for AI inference. EnCharge AI is working to make a chip that enables enhanced privacy but can also operate on very little power. This will make it suitable for military applications like satellites and off-grid surveillance equipment. The company expects to ship the chips in 2025.

AI models will always rely on the cloud for some applications, but new investment and interest in improving edge computing could bring faster chips, and therefore more AI, to our everyday devices. If edge chips get small and cheap enough, we’re likely to see even more AI-driven “smart devices” in our homes and workplaces. Today, AI models are mostly constrained to data centers.

“A lot of the challenges that we see in the data center will be overcome,” says EnCharge AI cofounder Naveen Verma. “I expect to see a big focus on the edge. I think it’s going to be critical to getting AI at scale.”

Big Tech enters the chipmaking fray

In industries ranging from fast fashion to lawn care, companies are paying exorbitant amounts in computing costs to create and train AI models for their businesses. Examples include models that employees can use to scan and summarize documents, as well as externally facing technologies like virtual agents that can walk you through how to repair your broken fridge. That means demand for cloud computing to train those models is through the roof. 

The companies providing the bulk of that computing power are Amazon, Microsoft, and Google. For years these tech giants have dreamed of increasing their profit margins by making chips for their data centers in-house rather than buying from companies like Nvidia, a giant with a near monopoly on the most advanced AI training chips and a value larger than the GDP of 183 countries. 

Amazon started its effort in 2015, acquiring startup Annapurna Labs. Google moved next in 2018 with its own chips called TPUs. Microsoft launched its first AI chips in November, and Meta unveiled a new version of its own AI training chips in April.

That trend could tilt the scales away from Nvidia. But Nvidia doesn’t only play the role of rival in the eyes of Big Tech: regardless of their own in-house efforts, cloud giants still need its chips for their data centers. That’s partly because their own chipmaking efforts can’t fulfill all their needs, but it’s also because their customers expect to be able to use top-of-the-line Nvidia chips.

“This is really about giving the customers the choice,” says Rani Borkar, who leads hardware efforts at Microsoft Azure. She says she can’t envision a future in which Microsoft supplies all chips for its cloud services: “We will continue our strong partnerships and deploy chips from all the silicon partners that we work with.”

As cloud computing giants attempt to poach a bit of market share away from chipmakers, Nvidia is also attempting the converse. Last year the company started its own cloud service so customers can bypass Amazon, Google, or Microsoft and get computing time on Nvidia chips directly. As this dramatic struggle over market share unfolds, the coming year will be about whether customers see Big Tech’s chips as akin to Nvidia’s most advanced chips, or more like their little cousins. 

Nvidia battles the startups 

Despite Nvidia’s dominance, there is a wave of investment flowing toward startups that aim to outcompete it in certain slices of the chip market of the future. Those startups all promise faster AI training, but they have different ideas about which flashy computing technology will get them there, from quantum to photonics to reversible computation. 

But Murat Onen, the 28-year-old founder of one such chip startup, Eva, which he spun out of his PhD work at MIT, is blunt about what it’s like to start a chip company right now.

“The king of the hill is Nvidia, and that’s the world that we live in,” he says.

Many of these companies, like SambaNova, Cerebras, and Graphcore, are trying to change the underlying architecture of chips. Imagine an AI accelerator chip as constantly having to shuffle data back and forth between different areas: a piece of information is stored in the memory zone but must move to the processing zone, where a calculation is made, and then be stored back to the memory zone for safekeeping. All that takes time and energy. 

Making that process more efficient would deliver faster and cheaper AI training to customers, but only if the chipmaker has good enough software to allow the AI training company to seamlessly transition to the new chip. If the software transition is too clunky, model makers such as OpenAI, Anthropic, and Mistral are likely to stick with big-name chipmakers.That means companies taking this approach, like SambaNova, are spending a lot of their time not just on chip design but on software design too.

Onen is proposing changes one level deeper. Instead of traditional transistors, which have delivered greater efficiency over decades by getting smaller and smaller, he’s using a new component called a proton-gated transistor that he says Eva designed specifically for the mathematical needs of AI training. It allows devices to store and process data in the same place, saving time and computing energy. The idea of using such a component for AI inference dates back to the 1960s, but researchers could never figure out how to use it for AI training, in part because of a materials roadblock—it requires a material that can, among other qualities, precisely control conductivity at room temperature. 

One day in the lab, “through optimizing these numbers, and getting very lucky, we got the material that we wanted,” Onen says. “All of a sudden, the device is not a science fair project.” That raised the possibility of using such a component at scale. After months of working to confirm that the data was correct, he founded Eva, and the work was published in Science.

But in a sector where so many founders have promised—and failed—to topple the dominance of the leading chipmakers, Onen frankly admits that it will be years before he’ll know if the design works as intended and if manufacturers will agree to produce it. Leading a company through that uncertainty, he says, requires flexibility and an appetite for skepticism from others.

“I think sometimes people feel too attached to their ideas, and then kind of feel insecure that if this goes away there won’t be anything next,” he says. “I don’t think I feel that way. I’m still looking for people to challenge us and say this is wrong.”