- Tuesday, March 27, 2018 at 12:10PM - 1:00PM
- Room 129
- Open To The YLS Community Only
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Complex medical algorithms are increasingly important to modern medicine. As health data are collected in greater and greater amounts, sophisticated algorithms based on those data can drive medical innovation, improve the process of care, and increase efficiency. Those algorithms, however, vary widely in quality; some are accurate and powerful, while others may be riddled with error or based on faulty science. Complicating the picture, many powerful algorithms are based on machine-learning techniques that render their workings opaque. Patients, doctors, and insurers face substantial difficulties in identifying high-quality algorithms, because they lack both expertise and the proprietary information needed for that evaluation. This situation calls for regulatory oversight to ensure safety and quality. But that oversight needs to be appropriately tailored. Rigid oversight is likely to stifle innovation and to block the development of more flexible, up-to-date algorithms. Instead,regulators should combine a more adaptive regulatory approach with requirements that algorithm developers disclose broad information about their algorithms. This disclosure would allow regulatory oversight to be supplemented by evaluation by doctors, insurers, and third-party validators. Robust post-market surveillance would allow algorithms to be watched as they perform in the clinic and also improved as new data are generated. Medical algorithms have tremendous potential but ensuring that such potential is developed in high-quality ways demands a carefully balanced and a role for regulators that mediates—but does not dominate—the rapidly developing industry.
Nicholson Price is an Assistant Professor of Law at the University of Michigan Law School. Before joining Michigan Law, he was an Assistant Professor at the University of New Hampshire School of Law. He holds a PhD in Biological Sciences and a JD, both from Columbia, and an AB from Harvard. He clerked for the Honorable Carlos T. Bea on the United States Court of Appeals for the Ninth Circuit, and was then appointed as an Academic Fellow at the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School. Nicholson teaches patents and health law, and studies innovation in the life sciences, with a recent focus on big data and machine learning in medicine. He recommends reading Brust, Bujold, and Butcher. His work has appeared in Nature, Science, Nature Biotechnology, the Michigan Law Review, and elsewhere. Nicholson is cofounder of Regulation and Innovation in the Biosciences and co-chair of the Junior IP Scholars Association.