Leo Celi and the 'Holy Grail of Personalized Medicine'

Danny Funt
APRIL 16, 2018
personalized medicine,precision medicine clinician,leo celi mit,hca news
Leo Celi, MD, is striving to advance precision medicine. Can he help transform healthcare?

AN AWAKENING CAN COME IN A FLASH, or it can occur over years, as dogma gradually breaks down in the face of data. For Leo Anthony Celi, MD, there was never a “eureka moment,” as he puts it, during his journey from studying medicine in the Philippines to becoming clinical research director at the Massachusetts Institute of Technology (MIT) Laboratory of Computational Physiology. Instead, it took rigorous training, along with extensive experience in clinical practice, before he recognized that the art of medicine can be woefully unscientific.

Celi, 51, says that realization can be “very disturbing.” He could have found it demoralizing too. Yet colleagues describe an investigator, professor, and physician with seemingly boundless enthusiasm. “Frankly, I don’t think I know anyone who is as energetic as he is,” says Peter Szolovits, PhD, who has worked at MIT for more than 30 years and is now head of its Clinical Decision Making Group, where he collaborates frequently with Celi. “I suspect he’ll continue to work like that when he’s 80.”

It might take that long before Celi’s vision for healthcare is even partially realized. The problem with the art of medicine is that it varies from doctor to doctor. As Szolovits explains, “What fraction of the clinical decisions you’ll make as a practicing doctor have had randomized clinical trials? If you’re an optimist, it’s 10% to 15%.” After more than 2 decades working in the intensive care unit (ICU), Celi knows this firsthand. “When it comes to what should I do for this 86-year-old gentleman in front of me with all these chronic conditions, it’s all guessing because there was no experiment that only enrolled 86-year-old men with his conditions,” he says. “That’s why we see so much variation in care.”

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“How can we make the practice of medicine more transparent and less likely to be affected by bias?” Celi asks. “To me, the only way to do that is by partnering with computers that can process a voluminous amount of data so much better than humans can.”

Virtually every industry is integrating data science, and practitioners in those fields often feel as though their expertise is under attack. It’s compelling to hear Celi speak on the fallibility of physicians in light of his credentials: Along with master’s degrees in public health from Harvard University and biomedical informatics from MIT, he completed specialized residency fellowships at the Cleveland Clinic, Stanford University, and Harvard University. “People are always paranoid that it’s going to be doctors versus computers,” Celi says. “If I were a patient, I would go to a doctor with a computer.”

Celi and his team foresee an optimal version of doctors with computers, dynamic clinical data mining. They imagine a system in which the “collective experience” of every possible patient on earth is aggregated and analyzed, as they’ve written. “This approach would interrogate data to suggest next-step options and weigh the risks and benefits of a treatment or test for a specific patient.” It would be, in short, “the Holy Grail of personalized medicine.”

That concept is made possible by electronic medical records (EMRs) and made impossible, for now, by the widespread reluctance to share patient data. One remarkable exception is being modeled by the lab at MIT where Celi works, using data from the ICU at Beth Israel Deaconess Medical Center in Boston, where he practices. The lab compiled elaborate data from more than 50,000 hospital admissions and has made the database accessible, for free, to thousands of investigators and students around the world. Granted, nobody can form conclusive insights by studying a decade’s worth of patient data from 1 unit at 1 hospital, but the database has been an amazing resource for exploring research questions and—more important—demonstrating how big data and machine learning could radically augment the wisdom behind treatment decisions.

From residents at Beth Israel Deaconess to professors at MIT, people who know Celi rave about his ability to facilitate collaboration among clinicians, data scientists, engineers, statisticians, and whoever else is needed for a project to succeed. In the ICU, he learned how the wellbeing of patients depends on a “collaborative culture,” he says. That’s also the only way forward to healthcare’s holy grail.

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