Regulating the Off-Label Use of Artificial Intelligence and Machine Learning-Enabled Medical Devices
Rachel Davis | 26 Vand. J. Ent. & Tech. L. 771 (2024)
Through machine learning (ML) developments, medical devices are gaining more autonomous functions and taking on more central roles in medical care. Many scholars believe that artificial intelligence (AI) will revolutionize the healthcare industry, but the technology brings several concerns that implicate data privacy, patient security and safety, and professional responsibility. The Federal Drug Administration (FDA) acknowledged this fact, publishing proposed guidance in 2023 on artificial intelligence and machine learning (AI/ML) medical device approval that would tighten device regulation upfront and enhance supervision throughout the regulatory process. While some have addressed the premarket approval process or tort liability frameworks for artificial intelligence-enabled devices, this Note focuses on the regulatory concerns arising from off-label use of AI/ML-enabled medical devices. This Note agrees with FDA and other scholars that the current legal system does not support the proper use of AI/ML-enabled medical devices. To remedy that lack of systemic support, this Note considers which agencies, if any, have the proper regulatory authority to handle the matter and challenges the idea that nonbinding guidance is the proper regulatory vehicle for enforcement. Ultimately, this Note argues for a multilevel regulatory framework promulgated under the formal rulemaking process, state regulatory procedure, and private regulation.