We can all agree that FDA has the right to set expectations for efficient and appropriate interaction with their review teams. However, FDA’s latest updates to the Q-sub guidance create more confusion than clarity and reveal frustrations at FDA with how industry is using the pre-submission program. As medical product development continues to become more complex along with the regulatory pathways we use to get them to market, FDA needs to find a balance between setting boundaries and putting up barriers to communication.
Read MoreA recent Northeastern University panel discussion about about the history and future of governance in artificial intelligence got me thinking about harmonization of medical device regulatory policy and wondering why it is so hard to do. As medical device technology is advancing at breakneck speed to bring AI-driven medical devices to patients and practitioners, we are seeing a rapid increase in policy implementation and legislation all intended to govern the use of AI in medical devices - but without much harmonization. Similar lack of harmonization in device classification, quality systems, and RWD/RWE governance have created barriers and costs to industry. With IMDRF being only a voluntary-based collaborative organization, what can be done to facilitate global harmonization of medical device regulation?
Read MoreAt the October NORD conference, Jeff Shuren suggested that AI-driven medical devices could be designed and evaluated using an FDA AI Assurance Lab. He suggested that this lab could house quality data on which AI algorithms could be trained. But, is this idea too good to be true? Where will the data come from? What therapeutic areas will it include? And will industry play nice in FDA’s AI Assurance Lab sandbox? Given the need for rational, consistent and transparent AI regulatory policy, this could be a great idea. But, the practical application of such a plan is unclear.
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