FDA prepares to regulate AI in medical devices

As medical devices are increasingly being touched by new AI innovations, the FDA will soon have to grapple with the reality of regulating “living things” in a new way, according to a report from Roll Call. Looking into the future, traditional means of regulation on medical devices won’t work for new inventions powered by AI.

Now, the FDA is currently evaluating an approach of evaluating medical device companies, including organizational culture of the maker, rather than simply the device or equipment. The FDA could assess machine learning practices, what data the AI systems are trained on and how algorithms are fine-tuned. The monitoring process and performance assessment would also be part of the picture.

However, the agency’s history with medical device regulation “has been found waiting” in some cases, according to the report. Fast-track approvals for some medical devices have come under fire after consumers reported injuries for breast implants, mesh and surgical staplers. On the flip side, changes to AI algorithms could potentially require FDA review under future requirements.

See the full story below:

Amy Baxter

Amy joined TriMed Media as a Senior Writer for HealthExec after covering home care for three years. When not writing about all things healthcare, she fulfills her lifelong dream of becoming a pirate by sailing in regattas and enjoying rum. Fun fact: she sailed 333 miles across Lake Michigan in the Chicago Yacht Club "Race to Mackinac."

Around the web

Compensation for heart specialists continues to climb. What does this say about cardiology as a whole? Could private equity's rising influence bring about change? We spoke to MedAxiom CEO Jerry Blackwell, MD, MBA, a veteran cardiologist himself, to learn more.

The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals. 

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”