FDA unveils a framework for reviewing AI-based medical devices


As part of its pledge to put some rules and regulations in AI, the FDA released a discussion paper detailing how it plans to vet and approve AI medical devices without compromising quality or patient safety.

AI-based medical devices are growing in popularity and scope, Commissioner Scott Gottlieb, MD, said in a statement, but it’s difficult for an agency that has been vetting “locked” algorithms for years to develop a framework for reviewing technology that’s constantly adapting. Most AI devices the FDA has authorized to date involve static technology that’s modified by the manufacturer at intervals, rather than tech that continually evolves based on what it’s learning in real-time.

“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,” Gottlieb said. “A new approach to these technologies would address the need for the algorithms to learn and adapt when used in the real world.”

That new approach is said to be a more tailored fit than the FDA’s existing regulatory paradigm for software as a medical device. For more traditional devices, when modifications are made that might significantly alter the safety or effectiveness of the technology, a sponsor has to make a submission demonstrating the safety and effectiveness of the modifications. Officials can’t take the same approach with AI, since the software is ever-changing.

So, the first step in developing a framework for regulating AI-based devices is to outline information specific to devices the FDA might require for premarket review — including an algorithm’s performance, the manufacturer’s plan for modifications and the ability of the manufacturer to manage and control the risks of those modifications. The FDA might require manufacturers to submit what’s known as a predetermined change control plan — which is an outline of any anticipated modifications based on an algorithm’s retraining and update strategy, as well as a plan of action for completing those modifications in a safe, controlled manner.

In that sense, FDA’s main goal in developing this new framework is to assure that ongoing algorithm changes follow pre-specified performance objectives and change control plans, use a validation process that ensures improvements to the performance and safety of the AI software and include real-world performance monitoring.

“We’re exploring this approach because we believe that it will enable beneficial and innovative artificial intelligence software to come to market while still ensuring the device’s benefits continue to outweigh its risks,” Gottlieb added.

The FDA is asking for feedback from experts and stakeholders in the medical space to flesh out their rudimentary framework. Next steps will include issuing draft guidance informed by that feedback.