With a new effort, the US Food and Drug Administration is hoping to keep up with the onslaught of new products that rely on machine learning and similar approaches to gauge which people are sick, Wired reports. And these products can reach the regulatory approval stage faster than more traditional medical devices, it adds.
Bakul Patel tells Wired that he has a few ideas on how to keep FDA on top of the current. The agency is developing a unit dedicated to digital health that will be hiring a dozen engineers. And Patel, who is the associate center director, is considering revamping how such devices are approved.
As Wired notes, FDA typically focuses its scrutiny on products that are high risk, and Patel is envision a path in which products from new developers or ones with iffy track record get the most attention while those from more trusted developers get a little less. Wired likens it to how the TSA screens airport passengers.
"We're headed toward a zero code world, where AI writes it for you or you just say what you want and natural language processing takes care of the rest," Patel adds. "The pace will be tremendously faster than what we're seeing today. The question is, how do we align our regulations to that radically different development timeline?"