Doctor with a syringe on the background of DNA.
Steve, a 60-year-old resident of the DC area who works in manufacturing, was always physically fit. In college, he played lacrosse in Division I, the highest level of intercollegiate athletics in the United States. Later, he stayed active by swimming, biking, and running--up until something strange happened around two years ago.
"It was hard for me to even get upstairs. I wasted away."
Steve, who requested that his last name be withheld to protect his privacy, started to notice weakness first in his toes, then his knees. On a trip to the zoo, he had trouble keeping up. Then some months later, the same thing happened on a family hike. What was supposed to be a four-mile trek up to see a waterfall ended for him at the quarter-mile mark. He turned around and struggled back to the start just as everyone else was returning from the excursion.
Alarmed, he sought out one doctor after the next, but none could diagnose him. The disabling weakness continued to creep up his legs, and by the time he got in to see a top neurologist at Johns Hopkins University last January, he was desperate for help.
"It was hard for me to even get upstairs," he recalls. "I wasted away and had lost about forty-five pounds."
The neurologist, Dr. Michael Polydefkis, finally made the correct diagnosis based on Steve's rapid progression of symptoms, a skin and nerve biopsy, and a genetic test. It turned out that Steve had a rare inherited disease called hereditary transthyretin amyloidosis. Transthyretin is a common blood protein whose normal function is to transport vitamins and hormones in the body. When patients possess certain genetic mutations in the transthyretin gene, the resulting protein can misfold, clump and produce amyloid, an aggregate of proteins, which then interferes with normal function. Many organs are affected in this disease, but most affected are the nervous system, the GI tract, and the heart.
Dr. Michael Polydefkis, Steve's neurologist at Johns Hopkins Bayview Medical Center in Baltimore, MD.
(Courtesy of Dr. Polydefkis)
For the 50,000 patients like Steve around the world, the only treatment historically has been a liver transplant—a major, risky operation. The liver makes most of the transthyretin in a person's body. So if a person who carries a genetic mutation for a disease-causing form of transthyretin has their liver transplanted, the new liver will stop making the mutant protein. A few drugs can slow, but do not stop the disease.
Since it is a genetic condition, a regular "drug" can't tackle the problem.
"For almost all of medicine from the 18th century to today, drugs have been small molecules, typically natural, some invented by humans, that bind to proteins and block their functions," explains Dr. Phillip Zamore, chair of the department of Biomedical Sciences at the University of Massachusetts Medical School. "But with most proteins (including this one), you can't imagine how that would ever happen. Because even if it stuck, there's no reason to think it would change anything. So people threw up their hands and said, 'Unless we can find a protein that is "druggable" in disease X, we can't treat it.'"
To draw a car analogy, treating a disease like Steve's with a small molecule would be like trying to shut down the entire car industry when all you can do is cut the power cord to one machine in one local factory. With few options, patients like Steve have been at a loss, facing continual deterioration and disability.
"It's more obvious how to be specific because we use the genetic code itself to design the drug."
A Radical New Approach
Luckily, Dr. Polydefkis knew of an experimental drug made by a biotech company that Dr. Zamore co-founded called Alnylam Pharmaceuticals. They were doing something completely different: silencing the chemical blueprint for protein, called RNA, rather than targeting the protein itself. In other words, shutting down all the bad factories across the whole car industry at once – without touching the good ones.
"It's more obvious how to be specific," says Dr. Zamore, "because we use the genetic code itself to design the drug."
For Steve's doctor, the new drug, called patisiran, is a game changer.
"It's the dawn of molecular medicine," says Dr. Polydefkis. "It's really a miraculous development. The ability to selectively knock down or reduce the amount of a specific protein is remarkable. I tell patients this is science fiction that is now becoming reality."
A (Very) Short History
The strategy of silencing RNA as a method of guiding drug development began in 1998. Basic research took six years before clinical testing in humans began in 2004. Just a few months ago, in November, the results of the first double-blind, placebo-controlled phase III trials were announced, testing patisiran in patients--and they surpassed expectations.
"The results were remarkably positive," says Dr. Polydefkis. "Every primary and secondary outcome measure target was met. It's the most positive trial I have ever been associated with and that I can remember in recent memory."
FDA approval is expected to come by summer, which will mark the first official sanction of a drug based on RNA inhibition (RNAi). Experts are confident that similar drugs will eventually follow for other diseases, like familial hypercholesterol, lipid disorders, and breathing disorders. Right now, these drugs must get into the liver to work, but otherwise the future treatment possibilities are wide open, according to Dr. Zamore.
"It doesn't have to be a genetic disease," he says. "In theory, it doesn't have to be just one gene, although I don't think anyone knows how many you could target at once. There is no precedent for targeting two."
Dr. Phillip Zamore, chair of the RNA Therapeutics Institute at the University of Massachusetts Medical School.
(Courtesy of Dr. Zamore)
Alnylam, the leading company in RNAi therapeutics, plans to strategically design other new drugs based on what they have learned from this first trial – "so with each successive experience, with designing and testing, you get better at making more drugs. In a way, that's never happened before...This is a lot more efficient of a way to make drugs in the future."
And unlike gene therapy, in which a patient's own genetic code is permanently altered, this approach does not cause permanent genetic changes. Patients can stop taking it like any other drug, and its effects will vanish.
How Is Steve?
Last February, Steve started on the drug. He was granted early access since it is not yet FDA-approved and is still considered experimental. Every 21 days, he has received an IV infusion that causes some minor side effects, like headaches and facial flushing.
"The good news is, since I started on the drug, I don't see any more deterioration other than my speech."
So far, it seems to be effective. He's gained back 20 pounds, and though his enunciation is still a bit slurred, he says that his neuropathy has stopped. He plans to continue the treatment for the rest of his life.
"The good news is, since I started on the drug, I don't see any more deterioration other than my speech," he says. "I think the drug is working, but would I have continued to deteriorate without the drug? I'm not really sure."
Dr. Polydefkis jumps in with a more confident response: "If you ask me, I would say 100 percent he would have kept progressing at a fairly rapid pace without the drug. When Steve says the neuropathy has stopped, that's music to my ears."
AI was integral to creating Moderna's mRNA vaccine against COVID.
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.
