In a recent post on the Covington Digital Health blog, we analyze FDA’s recently-released proposed regulatory approach for medical devices that use artificial intelligence (AI) and machine learning (ML), which we refer to here as the “AI Framework.” The AI Framework does not establish new requirements or an official policy, but rather was released by FDA to seek early input prior to the development of a draft guidance document. The AI Framework is FDA’s attempt to develop “an appropriate framework” for algorithms that learn and adapt in the real world.
As with FDA’s Pre-Cert Program, the AI Framework applies a total product lifecycle regulatory approach for regulating AI/ML-based software as a medical device (SaMD). FDA proposes a four-step approach.
- Culture of Quality and Organizational Excellence. Manufacturers of AI/ML-based SaMD should have an established quality system with good machine learning practices (GMLP).
- Initial Premarket Assurance of Safety and Effectiveness. The AI Framework anticipates that manufacturers would submit a plan for modifications as part of initial premarket review for an AI/ML-based SaMD. The initial plan for modifications would include the types of anticipated modifications, SaMD Pre-Specifications (SPS), and the associated methodology, the Algorithm Change Protocol (ACP), used to implement the changes in a controlled manner.
- Modifications after Initial Review. The AI Framework proposes an approach to manage risks from AI/ML modifications. FDA expects manufacturers to evaluate modifications based on risks to patients. If a modification is outside of agreed SPS and ACP but does not lead to a new intended use, FDA may conduct a “focused review” of the proposed SPS and ACP. If a modification is beyond the intended use for which the SaMD was previously authorized, manufacturers may need to submit a new premarket submission.
- Real World Performance Monitoring. FDA expects manufacturers to periodically report updates that were implemented as part of approved SPS and ACP and performance metrics for SaMD. FDA also expects manufacturers to be transparent about notifying users of updates. Manufacturers should monitor the real-world performance of AI/ML-based SaMD.
