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FDA officials outline perspectives on regulating AI in healthcare
Three senior officials from the U.S. Food and Drug Administration (FDA) published an article in The Journal of the American Medical Association (JAMA) that shares the agency’s perspectives on regulating artificial intelligence (AI) in healthcare and biomedicine. The article was authored by FDA Commissioner Robert Califf, Senior Clinical Advisor for Chronic Disease Haider Warraich, and Director of the Digital Health Center of Excellence within the Center for Devices and Radiological Health Troy Tazbaz.
The article outlines 10 concepts to consider “as the regulatory system adapts to address” rapidly evolving AI technology. According to the authors, the FDA will continue to “play a central role in ensuring safe, effective, and trustworthy AI tools,” but industry stakeholders will also need to take an interest in identifying and addressing irresponsible actors. In addition, stakeholders will need to participate in developing and optimizing the tools needed to “assess the ongoing safety and effectiveness of AI.”
Top concepts for regulating AI
The FDA approved the first partially AI-enabled medical device in 1995. Since then, the agency has authorized approximately 1,000 medical devices that employ AI technology. With the rapid pace of technological advancement and the growing use of AI in medical devices and drug development, the FDA officials outlined 10 concepts to guide the regulation of AI:
- AI regulation within the broader U.S. government and global context – Rules governing AI need to align with the broader U.S. legislative system while also ensuring compatibility with global standards.
- Keeping up with the pace of change in AI – The development, deployment, and use of AI-enabled products will require an “adaptive, science-based regulatory scheme to prevent harm while also supporting innovation that optimizes their benefits.”
- Flexible approaches across the spectrum of AI models – AI rules must be flexible and risk-based and will require “careful consideration and adaption” depending on intended use of AI systems.
- The central importance of AI life cycle management – AI performance should be monitored in the environment in which it is being used. This will require more approaches and tools to further refine AI evaluation because “an unmonitored AI system deployed in practice could do significant harm.”
- The responsibilities of regulated industries – The evolution of AI illustrates a major quality and regulatory dilemma, as the scale of effort needed to conduct recurrent evaluation to assess the safety and effectiveness of many AI models could be beyond any current FDA regulatory scheme.
The officials also offered concepts on the use of AI in medical product development; preparing for the unknowns of large language models (LLMs) and generative AI; maintaining robust supply chains; finding the balance between Big Tech, start-ups, and academia; and the tension between using AI to optimize financial returns versus improving health outcomes.
Looking ahead
The JAMA article does not have any legal or regulatory implications, but it can provide valuable insights for medical device and pharmaceutical businesses to better understand the FDA’s likely approach to regulating AI. Businesses throughout the healthcare ecosystem should review the publication and pay particular attention to the FDA’s emphasis on the role of industry in supporting the responsible development of AI systems. While AI regulation continues to evolve, this publication serves as a useful resource for understanding the direction it may take.
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