FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine
Abstract
Importance Advances in artificial intelligence (AI) must be matched by efforts to better understand and evaluate how AI performs across health care and biomedicine as well as develop appropriate regulatory frameworks. This Special Communication reviews the history of the US Food and Drug Administration's (FDA) regulation of AI; presents potential uses of AI in medical product development, clinical research, and clinical care; and presents concepts that merit consideration as the regulatory system adapts to AI's unique challenges. Observations The FDA has authorized almost 1000 AI-enabled medical devices and has received hundreds of regulatory submissions for drugs that used AI in their discovery and development. Health AI regulation needs to be coordinated across all regulated industries, the US government, and with international organizations. Regulators will need to advance flexible mechanisms to keep up with the pace of change in AI across biomedicine and health care. Sponsors need to be transparent about and regulators need proficiency in evaluating the use of AI in premarket development. A life cycle management approach incorporating recurrent local postmarket performance monitoring should be central to health AI development. Special mechanisms to evaluate large language models and their uses are needed. Approaches are necessary to balance the needs of the entire spectrum of health ecosystem interests, from large firms to start-ups. The evaluation and regulatory system w…
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Without appropriate regulation and inclusive planning, the risk of exacerbating health inequities remains high, particularly in underserved or digitally marginalized populations.
“However, without appropriate regulation and inclusive planning, the risk of exacerbating health inequities remains high—particularly in underserved or digitally marginalized populations [109,110].”
From Barriers and Facilitators to Artificial Intelligence Implementation in Diabetes Management from Healthcare Workers’ Perspective: A Scoping Review (2025) · cites this paper as [110]
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- Authors
- Warraich, H. J., Tazbaz, T., & Califf, R. M.
- Affiliations
- United States Food and Drug Administration (US)
- Corresponding author
- Warraich, Haider J.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2025-01-21
- Volume
- 333
- Issue
- 3
- Pages
- 241
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W4403420201
- Cited by
- 332
- References
- 36
- Citations by year
- 2026: 164 · 2025: 157 · 2024: 11
- FWCI
- 7.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Healthcare Regulation
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- AI regulation, AI-enabled medical devices, large language models, life cycle management, regulatory oversight, patient outcomes, international regulatory coordination
- MeSH terms
- Artificial Intelligence, Delivery of Health Care, Humans, United States, United States Food and Drug Administration, Drug Approval, Device Approval, Government Regulation, Biomedical Research, History, 20th Century, History, 21st Century
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