April 17, 2019
The Food and Drug Administration announced that it is developing a framework for regulating artificial intelligence products used in medicine that continually adapt based on new data, according to reporting by Casey Ross in STAT.
The agency’s outgoing commissioner, Scott Gottlieb, released a white paper that sets forth the broad outlines of the FDA’s proposed approach to establishing greater oversight over this rapidly evolving segment of AI products.
The white paper describes criteria the agency proposes to use to determine when medical products that rely on artificial intelligence will require FDA review before being commercialized.
The review may examine the underlying performance of a product’s algorithms, a manufacturer’s plan to make modifications, and the manufacturer’s ability to manage the risks associated with any modifications.
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“A new approach to these technologies would address the need for the algorithms to learn and adapt when used in the real world,” Gottlieb wrote in a statement accompanying the white paper. “It would be a more tailored fit than our existing regulatory paradigm for software as a medical device.”
The paper is the first step in a months-long process, in which the FDA will collect input from the public and a variety of stakeholders in medicine before finalizing a policy on regulating adaptive AI systems.
The FDA has already approved medical devices that rely on so-called “locked algorithms,” or those that do not change each time an algorithm is used, but instead are changed by a manufacturer at intervals, using specific training data and a validation process to ensure proper functioning of the system. Among the devices approved last year were a device used to detect diabetic retinopathy, a degenerative eye disease, and another designed to alert providers of a potential stroke in patients.