Whitepaper on Good Practices for AI

by TLM

Big news from FDA and Xavier Health regarding use of AI

FDA made bold statements at the Xavier Health AI Summit last week. For those companies struggling with the concept of how to validate a Continuously Learning System (CLS for of AI) for process improvement there is big news. FDA CDRH representatives Cisco Vicenty (FDA Program Manager, Case for Quality, Office of Compliance) and Bakul Patel (FDA, Associate Center Director for Digital Health) were in attendance and speaking on behalf of FDA. Cisco indicated that companies using a data lake from calibrated instruments and validated processes, equipment, and systems need only verify that the AI is performing as intended. It would not have to be further validated, but verified. Cisco and Bakul encouraged companies to speak with FDA about their specific use cases and intentions for utilizing AI and verifying AI as a tool so that any issues could be discussed. For many in attendance this resolved a looming problem that they were facing.

Furthermore FDA stated that companies will not be forced to use AI for process improvement but possibly asked as an analogy, why use a typewriter when a computer is so much better? The pharmaceutical and medical device industries will be encouraged to utilize AI where possible to improve efficiency and identify areas for process improvement. FDA also had hopes that AI could in the future be used to predict and eliminate or reduce drug or medical device shortages or adverse events. It could also be used by FDA and industry to improve approval times.

FDA representatives on the Fireside Chat panel also discussed the fact that AI would not generate sweeping changes to the regulations. AI is seen simply as a tool.

Xavier Health announced at the AI Summit the release of a new white paper titled, Perspectives and Good Practices for AI and Continuously Learning Systems in Healthcare, August 2018. “This paper focuses on identifying unique attributes, constraints and potential best practices towards what might represent ‘good’ development for Continuously Learning Systems (CLS) AI systems with applications ranging from pharmaceutical applications for new drug development and research to AI enabled smart medical devices. It should be noted that although the emphasis of this paper is on CLS, some of these issues are common to all AI products in healthcare.”

To Request Our Free Good Practices for AI and CLS in Healthcare White Paper please click the link below.