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# Get Involved with FDA on AI/ML: Attorneys
- URL: https://www.fdaweb.com/get-involved-with-fda-on-ai-ml-attorneys/
- Published: 2024-04-23T12:00:00.000Z
- Updated: 2026-09-14T14:29:00.000Z
- Author: David McFarland
- Tags: Drugs, Devices, #legacy-id-D5156826

Three Alston Bird attorneys say there are several steps companies regulated by FDA should take to engage with the agency on its artificial intelligence/machine learning (AI/ML) regulatory activities. Writing in their firm’s *FDA/Food, Drug, & Device Advisory*, the three [say](https://www.alston.com/en/insights/publications/2024/04/how-the-fda-is-keeping-up-with-ai?ref=fdaweb.com) companies should:

- review and comment on draft AI/ML guidances that should soon be issued on topics including methods to test, validate, and prepare AI/ML marketing submissions; recommendations for predetermined change control plans for AI-enabled device software functions; and lifecycle management considerations;
- request interactive pre-submission meetings with agency product Centers to educate them on AI technologies and seek FDA listing of clinical and product performance data requirements;
- monitor the dockets opened by FDA to accept comments and information from industry and outside constituencies; and
- participate in upcoming industry workshops, Part 15 hearings, advisory committee meetings, and other opportunities to engage with FDA decision-makers.

The post discusses three policy papers on AI/ML the agency has issued in the last year and the draft regulatory framework it has proposed.

“FDA has been quick to acknowledge that it has a base of knowledge acquired by approval, authorization, or clearance of over 700 AI/ML devices,” the attorneys write.

They say that AI/ML policies will remain a “work in progress” for the agency, as it continues to reach out, review external comments, and monitor developments while reviewing applications for products incorporating AI/ML on a case-by-case basis using existing methodologies. Centers, they write, will depend on their ad hoc experience to develop general guidance documents based on their internal experience conducting AI/ML product reviews.