Biotech Pioneer Leroy Hood Continues to Chart New Territory Using AI and Genetic Codes
In biology, genetics, and bioengineering, Leroy Hood is a true giant. In 2015, Scientific American named him one of the ten most influential people in the field of biotechnology. Hood is credited with introducing the term systems biology and he advocates for what he refers to as P4 medicine: predictive, personalized, preventive, and participatory.
I met Lee, as he is widely known, thirty years ago at Caltech and recently had the privilege of hosting him for a DataRobot podcast. At 82, he’s still coming up with new ideas and looking for ways to transform healthcare.
Lee’s inspiration goes back to when he was six and his baby brother was born with Down syndrome. “I remember asking the physician at the time what caused it, and he had absolutely no idea whatsoever,” Lee recalled. “That intrigued me and stayed with me for the rest of my life.”
Early in his career, Lee was told that there are two types of scientists: those who are librarians, rewriting a book that had already been written and those who put themselves —and stay— on the cutting edge of science. Lee is obviously of the second type.
In fact, I think it’s safe to say he literally created a new scientific field, one that combines biology, chemistry, physics, and computer science. “That way you could develop ideas together, you could collaborate together,” he says. “Most importantly, you could learn one another’s language.”
Like all revolutionary ideas, it was met with resistance. Caltech declined. By the early 1990s, Roger Perlmutter, one of Lee’s former students and the founding chair of the Immunology Department at the University of Washington, suggested that Hood move to Seattle and launch a new program. The Department of Biotechnology became the first cross-disciplinary biology department.
Hood’s current focus is deploying AI to solve the riddles of the human genome. He hopes to use data from a massive biobank effort, first planned under the Obama administration and now known as All of Us, to map the genetic code of one million people. “The idea is that in five years, we’ll have an enormous amount of longitudinal data that will include blood analytes, that will include the gut microbiome, all of these kinds of things,” Hood told me. “As we accumulate these data, we’re going to identify more and more actionable possibilities, things that if a patient does them can either improve their wellness or let them avoid disease.”
Hood has tried this once before. He was cofounder of a company called Arivale, which analyzed the genes of some 5,000 people, but closed in 2019 due to financial problems. Hood sees enormous potential in the much larger dataset now being built by the All of Us project.
“We can create a knowledge lake which basically has all of the known data about Alzheimer’s,” he said. “Then we take the individual data from an Alzheimer’s patient and process it through this lake, and it will give us a therapeutic series of recommendations.
“We can make a physician in a small town in Montana basically equivalent to an Alzheimer’s expert by letting the AI do the analysis and then feeding it back to the physician in a digestible manner so he can respond to the needs of the patient. That’s one of my big visions for twenty-first century medicine.”
Hood hopes that better gene sequencing and AI can be combined to detect and treat diseases at their earliest stages, before they reach the point where their symptoms become complex and deeply embedded. With the new mass-decoding project, he told me, “We estimate we’ll be able to see 175,000 wellness-to-disease transitions. I’m really impatient to get going on this.”
It’s impressive to see Lee’s continued drive and determination to solve big problems in healthcare. Few people have made such a contribution to medicine and our well-being.To hear more about Lee’s work, check out Datarobot.com/podcast or https://datarobot.buzzsprout.com/. You can also listen everywhere you already enjoy podcasts, including Apple, Spotify, Stitcher, and Google.
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