Regulatory research priorities for AI use in the medicine lifecycle: a European perspective with global relevance

Abstract

Regulatory bodies play a central role in providing guidance that enables safe and effective use of artificial intelligence tools in medicine development and evaluation. Regulators can also act as catalysts for regulatory science research. To inform these efforts, a European-wide survey was conducted to solicit stakeholder perspectives on the priority areas for regulatory science research related to the use of artificial intelligence in the medicine lifecycle. Twenty-eight regulatory science research questions were developed covering seven thematic domains: (1) research integrity and intellectual property; (2) accuracy and reliability of AI tools; (3) data governance, confidentiality, and consent; (4) regulation and oversight; (5) ethics, fairness, and bias prevention; (6) resources and support for AI use; and (7) impact on jobs and skills. Within each domain, stakeholders ranked four research challenges. A total of 273 responses were collected from regulators, pharmaceutical industry professionals, patients and consumers, academics, and healthcare professionals. Rankings of research challenges frequently converged across stakeholder groups and levels of AI experience. The top-ranked research questions within each domain were weighted according to the overall importance ranking of each domain to identify a list of ten priority areas of research. The majority of the ten priority areas fell within the domains of “Accuracy & reliability of AI tools,” “Data governance, confidentiality, & consent,” and “Ethics, fairness, & bias prevention.” This list aims to support researchers and research funding bodies in addressing knowledge gaps on artificial intelligence in the medicines lifecycle.

Note

This is a preprint and is under peer review.