US FDA and Device AI/ML

The US FDA has announced steps toward a new regulatory framework to promote the

development of medical devices that use advanced artificial intelligence / machine

learning algorithms - AI algorithms that can learn from and act on data. They have

already authorized some devices having AI capabilities. Their AI Good Machine

Learning Practice lists 10 “guiding principles” for ML/AI¹ to apply FDA’s current

authorities in new ways to keep up with the rapid pace of innovation and still ensure

device safety and performance.

The Agency is looking beyond elemental “locked” algorithm AI devices – devices that

don’t continually adapt or learn - to “true” AI - machine learning algorithms that

continually evolve, often called “adaptive” or “continuously learning” algorithms, that

learn through real-world use. The FDA is exploring a framework to allow modifications

to algorithms to be made from real-world learning and adaptation, while still ensuring

safety and effectiveness of the software required for premarket review. They include the

algorithm’s performance, the added concerns for AI / ML software verification and

validation, the manufacturer’s plan for modifications, and the ability of the manufacturer

to manage and control risks of the modifications, including the software’s

"predetermined change control plan".

¹ https://www.fda.gov/medical-devices/software-medical-device-samd/good-machine-

learning-practice-medical-device-development-guiding-principles

-- jel@jelincoln.com