Biomedical engineer Kevin Zhao has a sensor in his arm and his chest that monitors his oxygen level in those tissues in real time.
Last month, at a conference celebrating DARPA, the research arm of the Defense Department, FBI Special Agent Edward You declared, "The 21st century will be the revolution of the life sciences."
Biomedical engineer Kevin Zhao has a sensor in his arm and chest that monitors his oxygen level in real time.
Indeed, four years ago, the agency dedicated a new office solely to advancing biotechnology. Its primary goal is to combat bioterrorism, protect U.S. forces, and promote warfighter readiness. But its research could also carry over to improve health care for the general public.
With an annual budget of about $3 billion, DARPA's employees oversee about 250 research and development programs, working with contractors from corporations, universities, and government labs to bring new technologies to life.
Check out these three current programs:
1) IMPLANTABLE SENSORS TO MEASURE OXYGEN, LACTATE, AND GLUCOSE LEVELS IN REAL TIME
Biomedical engineer Kevin Zhao has a sensor in his arm and his chest that monitors his oxygen level in those tissues in real time. With funding from DARPA for the program "In Vivo Nanoplatforms," he developed soft, flexible hydrogels that are injected just beneath the skin to perform the monitoring and that sync to a smartphone app to give the user immediate health insights.
A first-in-man trial for the glucose sensor is now underway in Europe for monitoring diabetics, according to Zhao. Volunteers eat sugary food to spike their glucose levels and prompt the monitor to register the changes.
"If this pans out, with approval from FDA, then consumers could get the sensors implanted in their core to measure their levels of glucose, oxygen, and lactate," Zhao said.
Lactate, especially, interests DARPA because it's a first responder molecule to the onset of trauma, sepsis, and potentially infection.
"The sensor could potentially detect rise of these [body chemistry numbers] and alert the user to prevent onset of dangerous illness."
2) NEAR INSTANTANEOUS VACCINE PROTECTION DURING A PANDEMIC
Traditional vaccines can take months or years to develop, then weeks to become effective once you get it. But when an unknown virus emerges, there's no time to waste.
This program, called P3, envisions a much more ambitious approach to stop a pandemic in its tracks.
"We want to confer near instantaneous protection by doing it a different way – enlist the body as a bioreactor to produce therapeutics," said Col. Matthew Hepburn, the program manager.
So how would it work?
To fight a pandemic, we will need 20,000 doses of a vaccine in 60 days.
If you have antibodies against a certain infection, you'll be protected against that infection. This idea is to discover the genetic code for the antibody to a specific pathogen, manufacture those pieces of DNA and RNA, and then inject the code into a person's arm so the muscle cells will begin producing the required antibodies.
"The amazing thing is that it actually works, at least in animal models," said Hepburn. "The mouse muscles made enough protective antibodies so that the mice were protected."
The next step is to test the approach in humans, which the program will do over the next two years.
But the hard part is actually not discovering the genetic code for highly potent antibodies, according to Hepburn. In fact, researchers already have been able to do so in two to four weeks' time.
"The hard part is once I have an antibody, a large pharma company will say in 2 years, I can make 100-200 doses. Give us 4 years to get to 20,000 doses. That's not good enough," Hepburn said.
To fight a pandemic, we will need 20,000 doses of a vaccine in 60 days.
"We have to fundamentally change the idea that it takes a billion dollars and ten years to make a drug," he concluded. "We're going to do something radically different."
3) RAPID DIAGNOSING OF PATHOGEN EXPOSURE THROUGH EPIGENETICS
Imagine that you come down with a mysterious illness. It could be caused by a virus, bacteria, or in the most extreme catastrophe, a biological agent from a weapon of mass destruction.
What if a portable device existed that could identify--within 30 minutes—which pathogen you have been exposed to and when? It would be pretty remarkable for soldiers in the field, but also for civilians seeking medical treatment.
This is the lofty ambition of a DARPA program called Epigenetic Characterization and Observation, or ECHO.
Its success depends on a biological phenomenon known as the epigenome. While your DNA is relatively immutable, your environment can modify how your DNA is expressed, leaving marks of exposure that register within seconds to minutes; these marks can persist for decades. It's thanks to the epigenome that identical twins – who share identical DNA – can differ in health, temperament, and appearance.
These three mice are genetically identical. Epigenetic differences, however, result in vastly different observed characteristics.
Reading your epigenetic marks could theoretically reveal a time-stamped history of your body's environmental exposures.
Researchers in the ECHO program plan to create a database of signatures for exposure events, so that their envisioned device will be able to quickly scan someone's epigenome and refer to the database to sort out a diagnosis.
"One difficult part is to put a timestamp on this result, in addition to the sign of which exposure it was -- to tell us when this exposure happened," says Thomas Thomou, a contract scientist who is providing technical assistance to the ECHO program manager.
Other questions that remain up in the air for now: Do all humans have the same epigenetic response to the same exposure events? Is it possible to distinguish viral from bacterial exposures? Does dose and duration of exposure affect the signature of epigenome modification?
The program will kick off in January 2019 and is planned to last four years, as long as certain milestones of development are reached along the way. The desired prototype would be a simple device that any untrained person could operate by taking a swab or a fingerprick.
"In an outbreak," says Dr. Thomou, "it will help everyone on the ground immediately to have a rapidly deployable machine that will give you very quick answers to issues that could have far-reaching ramifications for public health safety."
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.
