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FDA Issues Draft Guidance on Predetermined Change Control Plans for AI/Machine Learning-Enabled Medical Devices

By MedTech Intelligence Staff
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The CDRH notes that the goal of the guidance is to put safe and effective advancements in the hands of healthcare providers and users more quickly to help increase the pace of medical device innovation in the U.S. and enable more personalized medicine.

On March 30, the FDA’s Center for Devices and Radiological Health (CDRH) published a draft guidance, “Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions.” Per the FDA’s announcement, the draft guidance proposes a science-based approach to ensuring that AI/ML-enabled devices can be safely, effectively, and rapidly modified, updated, and improved in response to new data.

The goal of the guidance is to put safe and effective advancements in the hands of healthcare providers and users more quickly to help increase the pace of medical device innovation in the U.S. and enable more personalized medicine. In addition to across-the-board, or “global,” device updates, AI/ML-enabled devices could be more extensively and rapidly modified to learn and adapt to local conditions. Examples provided by the agency include diagnostic devices that could be built to adapt to the data and needs of individual healthcare facilities and therapeutic devices that could be built to learn and adapt to deliver treatments according to individual users’ particular characteristics and needs.

“We will continue to assure the safety and effectiveness of AI/ML-enabled devices throughout the total product lifecycle (TPLC), including through a Predetermined Change Control Plan for the device that would be reviewed and agreed to by the FDA,” said Brendan O’Leary, Deputy Director of the Digital Health Center of Excellence in the FDA’s CDRH. “Under the proposal in the draft guidance, a Predetermined Change Control Plan could enable both changes that are implemented manually and changes that are implemented automatically by the software. The plan would include a detailed description of the specific, planned device modifications; a description of the methodology that would be used to develop, validate, and implement those modifications—including describing how necessary information about these modifications will be clearly communicated to users; and an assessment of the benefits and risks of the planned modifications.”

As part of the FDA’s continued focus on advancing health equity, the draft guidance includes performance considerations with respect to race, ethnicity, disease severity, gender, age, and geographical considerations, as part of the ongoing development, validation, implementation, and monitoring of AI/ML-enabled devices. Notably, the draft guidance proposes to place a significant and increased emphasis on the importance of clearly communicating valuable information about these considerations to device users.

O’Leary noted that the draft guidance is informed by the considerable experience the FDA has gained by regulating AI/ML-enabled devices and, in recent years, exploring new regulatory frameworks for digital health medical devices. It builds on a proposed framework for AI/ML Software as a Medical Device outlined in the CDRH’s 2019 discussion paper and further described in its AI/ML-Based Software as a Medical Device Action Plan.

“Notably, in the draft guidance, we are proposing the Predetermined Change Control Plan concept for not only AI/ML-enabled Software as a Medical Device, but for all AI/ML-enabled device software functions, including software functions that are part of or control hardware medical devices,” said O’Leary.

Stakeholders can submit comments on the draft guidance and download the full draft guidance document here.

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