FDA refines its approach to AI-based software

The FDA’s new Digital Health Center of Excellence has released a document describing how it will henceforth oversee and evaluate software that incorporates AI and machine learning for medical applications.

The center, which launched in September as a part of the Center for Devices and Radiological Health (CDRH), says it will consider such incorporations as potential contributors to devices’ total lifecycle performance.

In its announcement of the plan’s release, FDA summarizes five primary actions it will now take:

1. Further developing the proposed regulatory framework, including through issuance of draft guidance on a predetermined change control plan (for software’s learning over time);

2. Supporting the development of good machine learning practices to evaluate and improve machine learning algorithms;

3. Fostering a patient-centered approach, including device transparency to users;

4. Developing methods to evaluate and improve machine learning algorithms; and

5. Advancing real-world performance monitoring pilots.

In introducing the eight-page plan, CDRH director Bakul Patel, MBA, notes the “enormous potential that [AI and machine learning] technologies have to improve patient care while delivering safe and effective software functionality that improves the quality of care that patients receive.”

He adds that the plan is likely to be modified or adjusted during implementation as potential issues arise around safety, access and other considerations.

FDA says the plan’s particulars are based on input from stakeholders who commented on an April 2019 discussion paper, “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning-Based Software as a Medical Device.”

Announcement here, action plan here.