How AI helped make mRNA vaccines
Story by Big Think
For most of history, artificial intelligence (AI) has been relegated almost entirely to the realm of science fiction. Then, in late 2022, it burst into reality — seemingly out of nowhere — with the popular launch of ChatGPT, the generative AI chatbot that solves tricky problems, designs rockets, has deep conversations with users, and even aces the Bar exam.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
When COVID-19 cases were surging in New York City in early spring, Chitra Mohan, a postdoctoral fellow at Weill Cornell, was overwhelmed with worry. But the pandemic was only part of her anxieties. Having come to the United States from India on a student visa that allowed her to work for a year after completing her degree, she had applied for a two-year extension, typically granted for those in STEM fields. But due to a clerical error—Mohan used an electronic signatureinstead of a handwritten one— her application was denied and she could no longerwork in the United States.
"I was put on unpaid leave and I lost my apartment and my health insurance—and that was in the middle of COVID!" she says.
Meanwhile her skills were very much needed in those unprecedented times. A molecular biologist studying how DNA can repair itself, Mohan was trained in reverse transcription polymerase chain reaction or RT-PCR—a lab technique that detects pathogens and is used to diagnose COVID-19. Mohan wanted to volunteer at testing centers, but because she couldn't legally work in the U.S., she wasn't allowed to help either. She moved to her cousin's house, hired a lawyer, and tried to restore her work status.
"I spent about $4,000 on lawyer fees and another $1,200 to pay for the motions I filed," she recalls. "I had to borrow money from my parents and my cousin because without my salary I just didn't have the $7,000 at hand." But the already narrow window of opportunity slammed completely shut when the Trump administration suspended issuing new visas for foreign researchers in June. All Mohan's attempts were denied. In August, she had to leave the country. "Given the recent work visa ban by the administration, all my options in the U.S. are closed," she wrote a bitter note on Twitter. "I have to uproot my entire life in NY for the past 6 years and leave." She eventually found a temporary position in Calcutta, where she can continue research.
Mohan is hardly alone in her visa saga. Many foreign scholars on H- and J-type visas and other permits that let them remain employed in America had been struggling to keep their rights to continue research, which in certain cases is crucial to battling the pandemic. Some had to leave the country, some filed every possible extension to buy time, and others are stuck in their home countries, unable to return. The already cumbersome process of applying for visas and extensions became crippled during the lockdowns. But in June, when President Trump extended and expanded immigration restrictions to cut the number of immigrant workers entering the U.S., the new limits left researchers' projects and careers in limbo—and some in jeopardy.
"We have been a beneficiary of this flow of human capacity and resource investment for many generations—and this is now threatened."
Rakesh Ramachandran, whose computational biology work contributed to one of the first coronavirus studies to map out its protein structures—is stranded in India. In early March, he had travelled there to attend a conference and visit the American consulate to stamp his H1 visa for a renewal, already granted. The pandemic shut down both the conference and the consulates, and Ramachandran hasn't been able to come back since. The consulates finally opened in September, but so far the online portal has no available appointment slots. "I'm told to keep trying," Ramachandran says.
The visa restrictions affected researchers worldwide, regardless of disciplines or countries. A Ph.D. student in neuroscience, Morgane Leroux had to do her experiments with mice at Gladstone Institutes in America and analyze the data back home at Sorbonne University in France. She had finished her first round of experiments when the lockdowns forced her to return to Paris, and she hasn't been able to come back to resume her work since. "I can't continue the experiments, which is really frustrating," she says, especially because she doesn't know what it means for her Ph.D. "I may have to entirely change my subject," she says, which she doesn't want to do—it would be a waste of time and money.
But besides wreaking havoc in scholars' personal lives and careers, the visa restrictions had—and will continue to have—tremendous deleterious effects on America's research and its global scientific competitiveness. "It's incredibly short-sighted and self-destructing to restrict the immigration of scientists into the U.S.," says Benjamin G. Neel, who directs the Laura and Isaac Perlmutter Cancer Center at New York University. "If they can't come here, they will go elsewhere," he says, causing a brain drain.
Neel in his lab with postdocs
(Courtesy of Neel)
Neel felt the outcomes of the shortsighted policies firsthand. In the past few months, his lab lost two postdoctoral researchers who had made major strides in understanding the biology of several particularly stubborn, treatment-resistant malignancies. One postdoc studied the underlying mechanisms responsible for 90 percent of pancreatic cancers and half of the colon ones. The other one devised a new system of modeling ovarian cancer in mice to test new therapeutic drug combinations for the deadliest tumor types—but had to return home to China.
"By working around the clock, she was able to get her paper accepted, but she hasn't been able to train us to use this new system, which can set us back six months," Neel says.
Her discoveries also helped the lab secure about $900,000 in grants for new research. Losing people like this is "literally killing the goose that lays the golden eggs," Neel adds. "If you want to make America poor again, this is the way to do it."
Cassidy R. Sugimoto at Indiana University Bloomington, who studies how scientific knowledge is produced and disseminated, says that scientists are the most productive when they are free to move, exchange ideas, and work at labs with the best equipment. Restricting that freedom reduces their achievement.
"Several empirical studied demonstrated the benefits to the U.S. by attracting and retaining foreign scientists. The disproportional number of our Nobel Prize winners were not only foreign-born but also foreign-educated," she says. Scientific advancement bolsters the country's economic prowess, too, so turning scholars away is bad for the economy long-term. "We have been a beneficiary of this flow of human capacity and resource investment for many generations—and this is now threatened," Sugimoto adds—because scientists will look elsewhere. "We are seeing them shifting to other countries that are more hospitable, both ideologically and in terms of health security. Many visiting scholars, postdocs, and graduate students who would otherwise come to the United States are now moving to Canada."
It's not only the Ph.D. students and postdocs who are affected. In some cases, even well-established professors who have already made their marks in the field and direct their own labs at prestigious research institutions may have to pack up and leave the country in the next few months. One scientist who directs a prominent neuroscience lab is betting on his visa renewal and a green card application, but if that's denied, the entire lab may be in jeopardy, as many grants hinge on his ability to stay employed in America.
"It's devastating to even think that it can happen," he says—after years of efforts invested. "I can't even comprehend how it would feel. It would be terrifying and really sad." (He asked to withhold his name for fear that it may adversely affect his applications.) Another scientist who originally shared her story for this article, later changed her mind and withdrew, worrying that speaking out may hurt the entire project, a high-profile COVID-19 effort. It's not how things should work in a democratic country, scientists admit, but that's the reality.
Still, some foreign scholars are speaking up. Mehmet Doğan, a physicist at University of California Berkeley who has been fighting a visa extension battle all year, says it's important to push back in an organized fashion with petitions and engage legislators. "This administration was very creative in finding subtle and not so subtle ways to make our lives more difficult," Doğan says. He adds that the newest rules, proposed by the Department of Homeland Security on September 24, could further limit the time scholars can stay, forcing them into continuous extension battles. That's why the upcoming election might be a turning point for foreign academics. "This election will decide if many of us will see the U.S. as the place to stay and work or whether we look at other countries," Doğan says, echoing the worries of Neel, Sugimoto, and others in academia.
Dogan on Zoom talking to his fellow union members of the Academic Researchers United, a union of almost 5,000 Academic Researchers.
(Credit: Ceyda Durmaz Dogan)
If this year has shown us anything, it is that viruses and pandemics know no borders as they sweep across the globe. Likewise, science can't be restrained by borders either. "Science is an international endeavor," says Neel—and right now humankind now needs unified scientific research more than ever, unhindered by immigration hurdles and visa wars. Humanity's wellbeing in America and beyond depends on it.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
A company uses AI to fight muscle loss and unhealthy aging
There’s a growing need to slow down the aging process. The world’s population is getting older and, according to one estimate, 80 million Americans will be 65 or older by 2040. As we age, the risk of many chronic diseases goes up, from cancer to heart disease to Alzheimer’s.
BioAge Labs, a company based in California, is using genetic data to help people stay healthy for longer. CEO Kristen Fortney was inspired by the genetics of people who live long lives and resist many age-related diseases. In 2015, she started BioAge to study them and develop drug therapies based on the company’s learnings.
The team works with special biobanks that have been collecting blood samples and health data from individuals for up to 45 years. Using artificial intelligence, BioAge is able to find the distinctive molecular features that distinguish those who have healthy longevity from those who don’t.
In December 2022, BioAge published findings on a drug that worked to prevent muscular atrophy, or the loss of muscle strength and mass, in older people. Much of the research on aging has been in worms and mice, but BioAge is focused on human data, Fortney says. “This boosts our chances of developing drugs that will be safe and effective in human patients.”
How it works
With assistance from AI, BioAge measures more than 100,000 molecules in each blood sample, looking at proteins, RNA and metabolites, or small molecules that are produced through chemical processes. The company uses many techniques to identify these molecules, some of which convert the molecules into charged atoms and then separating them according to their weight and charge. The resulting data is very complex, with many thousands of data points from patients being followed over the decades.
BioAge validates its targets by examining whether a pathway going awry is actually linked to the development of diseases, based on the company’s analysis of biobank health records and blood samples. The team uses AI and machine learning to identify these pathways, and the key proteins in the unhealthy pathways become their main drug targets. “The approach taken by BioAge is an excellent example of how we can harness the power of big data and advances in AI technology to identify new drugs and therapeutic targets,” says Lorna Harries, a professor of molecular genetics at the University of Exeter Medical School.
Martin Borch Jensen is the founder of Gordian Biotechnology, a company focused on using gene therapy to treat aging. He says BioAge’s use of AI allows them to speed up the process of finding promising drug candidates. However, it remains a challenge to separate pathologies from aspects of the natural aging process that aren’t necessarily bad. “Some of the changes are likely protective responses to things going wrong,” Jensen says. “Their data doesn’t…distinguish that so they’ll need to validate and be clever.”
Developing a drug for muscle loss
BioAge decided to focus on muscular atrophy because it affects many elderly people, making it difficult to perform everyday activities and increasing the risk of falls. Using the biobank samples, the team modeled different pathways that looked like they could improve muscle health. They found that people who had faster walking speeds, better grip strength and lived longer had higher levels of a protein called apelin.
Apelin is a peptide, or a small protein, that circulates in the blood. It is involved in the process by which exercise increases and preserves muscle mass. BioAge wondered if they could prevent muscular atrophy by increasing the amount of signaling in the apelin pathway. Instead of the long process of designing a drug, they decided to repurpose an existing drug made by another biotech company. This company, called Amgen, had explored the drug as a way to treat heart failure. It didn’t end up working for that purpose, but BioAge took note that the drug did seem to activate the apelin pathway.
BioAge tested its new, repurposed drug, BGE-105, and, in a phase 1 clinical trial, it protected subjects from getting muscular atrophy compared to a placebo group that didn’t receive the drug. Healthy volunteers over age 65 received infusions of the drug during 10 days spent in bed, as if they were on bed rest while recovering from an illness or injury; the elderly are especially vulnerable to muscle loss in this situation. The 11 people taking BGE-105 showed a 100 percent improvement in thigh circumference compared to 10 people taking the placebo. Ultrasound observations also revealed that the group taking the durg had enhanced muscle quality and a 73 percent increase in muscle thickness. One volunteer taking BGE-105 did have muscle loss compared to the the placebo group.
Heather Whitson, the director of the Duke University Centre for the study of aging and human development, says that, overall, the results are encouraging. “The clinical findings so far support the premise that AI can help us sort through enormous amounts of data and identify the most promising points for beneficial interventions.”
More studies are needed to find out which patients benefit the most and whether there are side effects. “I think further studies will answer more questions,” Whitson says, noting that BGE-105 was designed to enhance only one aspect of physiology associated with exercise, muscle strength. But exercise itself has many other benefits on mood, sleep, bones and glucose metabolism. “We don’t know whether BGE-105 will impact these other outcomes,” she says.
The future
BioAge is planning phase 2 trials for muscular atrophy in patients with obesity and those who have been hospitalized in an intensive care unit. Using the data from biobanks, they’ve also developed another drug, BGE-100, to treat chronic inflammation in the brain, a condition that can worsen with age and contributes to neurodegenerative diseases. The team is currently testing the drug in animals to assess its effects and find the right dose.
BioAge envisions that its drugs will have broader implications for health than treating any one specific disease. “Ultimately, we hope to pioneer a paradigm shift in healthcare, from treatment to prevention, by targeting the root causes of aging itself,” Fortney says. “We foresee a future where healthy longevity is within reach for all.”