FDA Guidance Eases Burden for AI-Enabled Medical Device Changes

Public Policy & Regulation attorney John Vaughan was quoted in a Bloomberg Law article analyzing new guidance from the U.S. Food and Drug Administration (FDA) that aims to expedite review of artificial intelligence (AI)-enabled medical devices and software. AI-enabled and machine learning (ML) devices provide an array of services, from detecting diseases to taking measurements of clinical images, and the FDA has approved more than 1,000 such devices. However, any modifications that could affect a device's safety or effectiveness require premarket authorization, which can bog down development and slow product deployment. In the guidance, the FDA outlines how manufacturers can submit a predetermined change control plan (PCCP) to obtain preapproval for iterative, or minor, changes to devices after they're on the market. A PCCP could prove a welcome solution for the government and developers by reducing the regulatory burden on both sides. However, Mr. Vaughan and other life sciences professionals cautioned the FDA could still face a heavy workload to stay on top of a rapidly expanding field, and the amount of detail recommended for PCCPs could be "voluminous."

"It relieves the burden on FDA to constantly be reviewing or being notified of particularly minor changes," he said. "But, also, each AI platform is different and so it is a challenge for the agency to monitor modification to all of these different products."

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