New guidance on AI-enabled device software functions clarifies information FDA expects in marketing applications
Summary
Throughout, the guidance reflects FDA’s continuous efforts to foster good machine learning practices and provision of transparency to users and encourages sponsors to be mindful of all aspects that should go into developing and managing an AI-enabled device through the product’s lifecycle, starting early in the process. FDA also encourages sponsors to reference FDA-recognized voluntary consensus standards specific to software, such as AAMI CR34971 Guidance on the Application of ISO 14971 to Artificial Intelligence and Machine Learning. FDA discusses the importance of data management to promote generalizability of AI models to the intended use population(s) and to identify and mitigate biases. Finally, focusing on ensuring adequate device performance across the intended use population, FDA stresses the importance of appropriate subgroup analysis as a tool not only to support generalizability but also to identify – and subsequently inform users of – potential limitations. The draft guidance encourages obtaining FDA feedback should a sponsor elect to incorporate proactive performance monitoring as a means of risk control and/or to support their substantial equivalence argument.