FDA mulls new regulatory framework for AI-based medical devices

The Food and Drug Administration is considering a new regulatory framework to promote the development of safe and effective medical devices that leverage artificial intelligence algorithms.

FDA Commissioner Scott Gottlieb, MD, issued a written statement on Tuesday announcing that the agency was “taking the first step toward developing a novel and tailored approach to help developers bring artificial intelligence devices to market” by releasing a discussion paper on the topic.

“We anticipate several more steps in the future, including issuing draft guidance that’ll be informed by the feedback on today’s discussion paper,” said Gottlieb. “We encourage feedback and welcome a diversity of opinions and thoughtful discourse, which will contribute to building the foundation of this regulatory paradigm. As algorithms evolve, the FDA must also modernize our approach to regulating these products.”

According to Gottlieb, AI and machine learning have the potential to “fundamentally transform the delivery of healthcare” with algorithms “already being used to aid in screening for diseases and to provide treatment recommendations.”

In his statement, Gottlieb noted that the FDA approved several AI-based medical devices last year, including one for detecting diabetic retinopathy.

FDA-building.jpg

Also See: FDA clears AI-based system to detect diabetic retinopathy

However, Gottlieb pointed out that the technologies cleared by the agency so far are generally “locked” algorithms that “don’t continually adapt or learn every time the algorithm is used” and are manually modified by the manufacturer to incorporate learning or updates.

Where the FDA sees tremendous potential in healthcare are machine learning algorithms that continually evolve—called “adaptive” or “continuously learning” algorithms—that don’t need manual modification to incorporate learning or updates.

“We are exploring a framework that would allow for modifications to algorithms to be made from real-world learning and adaptation, while still ensuring safety and effectiveness of the software as a medical device is maintained,” according to Gottlieb. “It would be a more tailored fit than our existing regulatory paradigm for software as a medical device.”

“For traditional software as a medical device, when modifications are made that could significantly affect the safety or effectiveness of the device, a sponsor must make a submission demonstrating the safety and effectiveness of the modifications,” he added. “With artificial intelligence, because the device evolves based on what it learns while it’s in real world use, we’re working to develop an appropriate framework that allows the software to evolve in ways to improve its performance while ensuring that changes meet our gold standard for safety and effectiveness throughout the product’s lifecycle—from premarket design throughout the device’s use on the market.”

For reprint and licensing requests for this article, click here.