Harvard Law to Explore Legal Complexities of Precision Medicine, AI

The Ivy’s bioethics center will collaborate with colleagues at University of Copenhagen to develop frameworks around “black box” medicine.

Precision medicine and artificial intelligence (AI) are complicated by design: Both scientific fields rely on extreme specificity, complex equations, and forces that can’t be seen.

As both fields begin to alter the healthcare landscape, they could plant a number of legal landmines. Can algorithms or biomarkers be patented? Will centers be able to access the large data sets they need to perform accurate AI? What control over their data should patients have? And how will practice be affected by differing legal frameworks in the US and Europe?

A new collaborative initiative between Harvard Law School and the University of Copenhagen plans to explore those issues. Recently announced by the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard and the Center for Advanced Studies in Biomedical Innovation Law (CeBIL) at Copenhagen, the effort will be called the Project on Precision Medicine, Artificial Intelligence, and the Law (PMAIL). It will be led by Harvard Law School professor I. Glenn Cohen.

PMAIL will place a heavy focus on what it calls “black box medicine”—interventions based on algorithms so complex that they are either very difficult or impossible for humans to understand. For obvious reasons, such technologies will be difficult to validate and regulate.

According to an official announcement, the initiative will work for 5 years to try to create a comparative analysis of existing laws that pertain to such algorithms in both the US and Europe.

In a separate Q&A with a Harvard Law School publication, Cohen said that intellectual property will also be an important focus of PMAIL, citing cases like Mayo v. Prometheus Labs. He believes that and other recent court battles have, “undercut the protections an inventor can expect for algorithms which, in turn, may reduce the incentives of developers to refine the algorithms.”

Situations like those highlight the main challenge for PMAIL: In the current system, legal minds must interpret old laws as they apply to unheralded new technologies that the scholars themselves may not even understand. Cohen, in the same interview, said that the “purpose of PMAIL is to create a roadmap for ‘catching up’ our legal and regulatory systems,” to the new realities of medicine.

Cohen will be joined on the initiative by the Petrie-Flom Center’s executive director Carmel Schachar, University of Michigan assistant professor of law Nicholson Price, and the head of CeBIL at the University of Copenhagen, Timo Minssen. The Petrie-Flom Center will said it will also hire a fellow to work on PMAIL.

“Artificial intelligence and machine learning in medicine create tremendous possibilities of transforming health care for the better—but it’s so different from traditional medical technology that we need new tools to understand how it should be developed, regulated, and deployed in care settings,” Price, also a former Petrie-Flom Center fellow, said. “PMAIL aims to tackle exactly those issues and help develop those tools.”