FDA Releases Artificial Intelligence/Machine Learning Action Plan

Earlier this month, the FDA released its first Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan. 

As part of its breakthrough, the FDA pointed out some interesting aspects of its new policy area.

“Consistent with FDA’s longstanding commitment to develop and apply innovative approaches to the regulation of medical device software and other digital health technologies, in April of 2019, FDA published the “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) - Discussion Paper and Request for Feedback.” This paper described the FDA’s foundation for a potential approach to premarket review for artificial intelligence and machine learning-driven software modifications. The ideas delineated in the discussion paper leveraged practices from our current premarket programs and relied on the International Medical Device Regulators Forum’s risk categorization principles, the FDA’s benefit-risk framework, risk management principles described in the software modifications guidance, and the organization-based total product lifecycle approach also envisioned in the Digital Health Software Precertification (Pre-Cert) Pilot Program.

As part of this proposed framework, FDA described a “Predetermined Change Control Plan” in premarket submissions. This plan would include the types of anticipated modifications—referred to as the “SaMD Pre-Specifications”—and the associated methodology being used to implement those changes in a controlled manner that manages risks to patients —referred to as the “Algorithm Change Protocol.” In this approach, FDA expressed an expectation for transparency and real-world performance monitoring by manufacturers that could enable FDA and manufacturers to evaluate and monitor a software product from its premarket development through postmarket performance. This framework would enable FDA to provide a reasonable assurance of safety and effectiveness while embracing the iterative improvement power of artificial intelligence and machine learning-based software as a medical device.”

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