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.
A newly discovered brain cell may lead to better treatments for cognitive disorders
Swiss researchers have discovered a third type of brain cell that appears to be a hybrid of the two other primary types — and it could lead to new treatments for many brain disorders.
The challenge: Most of the cells in the brain are either neurons or glial cells. While neurons use electrical and chemical signals to send messages to one another across small gaps called synapses, glial cells exist to support and protect neurons.
Astrocytes are a type of glial cell found near synapses. This close proximity to the place where brain signals are sent and received has led researchers to suspect that astrocytes might play an active role in the transmission of information inside the brain — a.k.a. “neurotransmission” — but no one has been able to prove the theory.
A new brain cell: Researchers at the Wyss Center for Bio and Neuroengineering and the University of Lausanne believe they’ve definitively proven that some astrocytes do actively participate in neurotransmission, making them a sort of hybrid of neurons and glial cells.
According to the researchers, this third type of brain cell, which they call a “glutamatergic astrocyte,” could offer a way to treat Alzheimer’s, Parkinson’s, and other disorders of the nervous system.
“Its discovery opens up immense research prospects,” said study co-director Andrea Volterra.
The study: Neurotransmission starts with a neuron releasing a chemical called a neurotransmitter, so the first thing the researchers did in their study was look at whether astrocytes can release the main neurotransmitter used by neurons: glutamate.
By analyzing astrocytes taken from the brains of mice, they discovered that certain astrocytes in the brain’s hippocampus did include the “molecular machinery” needed to excrete glutamate. They found evidence of the same machinery when they looked at datasets of human glial cells.
Finally, to demonstrate that these hybrid cells are actually playing a role in brain signaling, the researchers suppressed their ability to secrete glutamate in the brains of mice. This caused the rodents to experience memory problems.
“Our next studies will explore the potential protective role of this type of cell against memory impairment in Alzheimer’s disease, as well as its role in other regions and pathologies than those explored here,” said Andrea Volterra, University of Lausanne.
But why? The researchers aren’t sure why the brain needs glutamatergic astrocytes when it already has neurons, but Volterra suspects the hybrid brain cells may help with the distribution of signals — a single astrocyte can be in contact with thousands of synapses.
“Often, we have neuronal information that needs to spread to larger ensembles, and neurons are not very good for the coordination of this,” researcher Ludovic Telley told New Scientist.
Looking ahead: More research is needed to see how the new brain cell functions in people, but the discovery that it plays a role in memory in mice suggests it might be a worthwhile target for Alzheimer’s disease treatments.
The researchers also found evidence during their study that the cell might play a role in brain circuits linked to seizures and voluntary movements, meaning it’s also a new lead in the hunt for better epilepsy and Parkinson’s treatments.
“Our next studies will explore the potential protective role of this type of cell against memory impairment in Alzheimer’s disease, as well as its role in other regions and pathologies than those explored here,” said Volterra.
Researchers claimed they built a breakthrough superconductor. Social media shot it down almost instantly.
Harsh Mathur was a graduate physics student at Yale University in late 1989 when faculty announced they had failed to replicate claims made by scientists at the University of Utah and the University of Wolverhampton in England.
Such work is routine. Replicating or attempting to replicate the contraptions, calculations and conclusions crafted by colleagues is foundational to the scientific method. But in this instance, Yale’s findings were reported globally.
“I had a ringside view, and it was crazy,” recalls Mathur, now a professor of physics at Case Western Reserve University in Ohio.
Yale’s findings drew so much attention because initial experiments by Stanley Pons of Utah and Martin Fleischmann of Wolverhampton led to a startling claim: They were able to fuse atoms at room temperature – a scientific El Dorado known as “cold fusion.”
Nuclear fusion powers the stars in the universe. However, star cores must be at least 23.4 million degrees Fahrenheit and under extraordinary pressure to achieve fusion. Pons and Fleischmann claimed they had created an almost limitless source of power achievable at any temperature.
Like fusion, superconductivity can only be achieved in mostly impractical circumstances.
But about six months after they made their startling announcement, the pair’s findings were discredited by researchers at Yale and the California Institute of Technology. It was one of the first instances of a major scientific debunking covered by mass media.
Some scholars say the media attention for cold fusion stemmed partly from a dazzling announcement made three years prior in 1986: Scientists had created the first “superconductor” – material that could transmit electrical current with little or no resistance. It drew global headlines – and whetted the public’s appetite for announcements of scientific breakthroughs that could cause economic transformations.
But like fusion, superconductivity can only be achieved in mostly impractical circumstances: It must operate either at temperatures of at least negative 100 degrees Fahrenheit, or under pressures of around 150,000 pounds per square inch. Superconductivity that functions in closer to a normal environment would cut energy costs dramatically while also opening infinite possibilities for computing, space travel and other applications.
In July, a group of South Korean scientists posted material claiming they had created an iron crystalline substance called LK-99 that could achieve superconductivity at slightly above room temperature and at ambient pressure. The group partners with the Quantum Energy Research Centre, a privately-held enterprise in Seoul, and their claims drew global headlines.
Their work was also debunked. But in the age of internet and social media, the process was compressed from half-a-year into days. And it did not require researchers at world-class universities.
One of the most compelling critiques came from Derrick VanGennep. Although he works in finance, he holds a Ph.D. in physics and held a postdoctoral position at Harvard. The South Korean researchers had posted a video of a nugget of LK-99 in what they claimed was the throes of the Meissner effect – an expulsion of the substance’s magnetic field that would cause it to levitate above a magnet. Unless Hollywood magic is involved, only superconducting material can hover in this manner.
That claim made VanGennep skeptical, particularly since LK-99’s levitation appeared unenthusiastic at best. In fact, a corner of the material still adhered to the magnet near its center. He thought the video demonstrated ferromagnetism – two magnets repulsing one another. He mixed powdered graphite with super glue, stuck iron filings to its surface and mimicked the behavior of LK-99 in his own video, which was posted alongside the researchers’ video.
VanGennep believes the boldness of the South Korean claim was what led to him and others in the scientific community questioning it so quickly.
“The swift replication attempts stemmed from the combination of the extreme claim, the fact that the synthesis for this material is very straightforward and fast, and the amount of attention that this story was getting on social media,” he says.
But practicing scientists were suspicious of the data as well. Michael Norman, director of the Argonne Quantum Institute at the Argonne National Laboratory just outside of Chicago, had doubts immediately.
Will this saga hurt or even affect the careers of the South Korean researchers? Possibly not, if the previous fusion example is any indication.
“It wasn’t a very polished paper,” Norman says of the Korean scientists’ work. That opinion was reinforced, he adds, when it turned out the paper had been posted online by one of the researchers prior to seeking publication in a peer-reviewed journal. Although Norman and Mathur say that is routine with scientific research these days, Norman notes it was posted by one of the junior researchers over the doubts of two more senior scientists on the project.
Norman also raises doubts about the data reported. Among other issues, he observes that the samples created by the South Korean researchers contained traces of copper sulfide that could inadvertently amplify findings of conductivity.
The lack of the Meissner effect also caught Mathur’s attention. “Ferromagnets tend to be unstable when they levitate,” he says, adding that the video “just made me feel unconvinced. And it made me feel like they hadn't made a very good case for themselves.”
Will this saga hurt or even affect the careers of the South Korean researchers? Possibly not, if the previous fusion example is any indication. Despite being debunked, cold fusion claimants Pons and Fleischmann didn’t disappear. They moved their research to automaker Toyota’s IMRA laboratory in France, which along with the Japanese government spent tens of millions of dollars on their work before finally pulling the plug in 1998.
Fusion has since been created in laboratories, but being unable to reproduce the density of a star’s core would require excruciatingly high temperatures to achieve – about 160 million degrees Fahrenheit. A recently released Government Accountability Office report concludes practical fusion likely remains at least decades away.
However, like Pons and Fleischman, the South Korean researchers are not going anywhere. They claim that LK-99’s Meissner effect is being obscured by the fact the substance is both ferromagnetic and diamagnetic. They have filed for a patent in their country. But for now, those claims remain chimerical.
In the meantime, the consensus as to when a room temperature superconductor will be achieved is mixed. VenGennep – who studied the issue during his graduate and postgraduate work – puts the chance of creating such a superconductor by 2050 at perhaps 50-50. Mathur believes it could happen sooner, but adds that research on the topic has been going on for nearly a century, and that it has seen many plateaus.
“There's always this possibility that there's going to be something out there that we're going to discover unexpectedly,” Norman notes. The only certainty in this age of social media is that it will be put through the rigors of replication instantly.