FDA Regulation of Artificial Intelligence/Machine Learning
José Mora is a Principal Consultant specializing in Manufacturing Engineering and Quality Systems. For over 30 years he has worked in the medical device and life sciences industry specializing in manufacturing, process development, tooling, and quality systems. Prior to working full time as a consulting partner for Atzari Consulting, José served as Director of Manufacturing Engineering at Boston Scientific and as Quality Systems Manager at Stryker Orthopedics, where he introduced process performance, problem-solving, and quality system methodologies. During that time he prepared a white paper on the application of lean manufacturing methods to the creation and management of controlled documents and a template for strategic deployment. José led the launch of manufacturing at a start-up urology products company as Director of Manufacturing for UroSurge, Inc. at the University of Iowa’s business incubator park in Coralville, IA, creating a world-class medical device manufacturing operation, with JIT, kanban systems, visual workplace, and lean manufacturing practices.
José worked for 10 years at Cordis Corporation, now a Cardinal Health company, where he led the successful tooling, process development and qualification of Cordis’ first PTA (percutaneous transluminal angioplasty) catheter. His medical device experience includes surgical instruments, PTA & PTCA dilatation and guiding catheters, plastic surgery implants and tissue expanders, urology implants and devices for the treatment of incontinence, delivery systems for brachytherapy, orthopedic implants and instruments, and vascular surgery grafts and textiles. During his time at Cordis, José managed the Maintenance and Facilities Department, taking that operation to a level rated as “tops” by the UK Department of Health and Social Services (DHSS) during one of their intensive audits. Jose managed Manufacturing Engineering as part of the Guiding Catheter Core Team of managers, a team that took the Cordis Guiding Catheter business to lead the market, bringing it up from fourth place. By introducing world-class techniques, the Guiding Catheter design and manufacturing was completely re-engineered for robust design and tooling, under Jose’s leadership. He was also instrumental and played a leadership role in the complete re-engineering of the Tooling Control System, including design drafting, the tool shop, and technical support. Wherever he has worked, he has a track record of introducing world-class methodologies such as Kepner-Tregoe, Taguchi techniques, Theory of Constraints, Lean Manufacturing, Five S (Visual Workplace), process validation to Global Harmonization Task Force standards, and similar approaches.
AI/ML will revolutionize medicine by making diagnosis and treatment more accessible and more effective. FDA has regulated medical software by means of regulation and guidance for years, however, AI/ML programs fall outside the scope of these regulations and guidance. This happens because the FDA approves the final, validated version of the software. The point of AI/ML is to learn and update the following deployment to improve performance. Thus the field version of the software is no longer the validated approved version.
We will discuss the current regulatory requirements, how they don’t control AI/ML adequately, and approaches FDA is considering for regulation in the near future. Your development program should conform to these concepts now because, with some modifications, they will probably become regulations. Following a discussion of possible future regulations, we will discuss, based on recently approved De Novo applications, how to get your AI/ML program approved now. Necessary submission documentation will be explained. This webinar is not a programming course but will explain the present and future regulatory requirements for AI/ML
- Total product life cycle approach to AI/ ML design
- Application of FDA software Pre Cert program to AI/ ML
- FDA discussion paper on AI/ML
- Database management
- QC of datasets
- Algorithm updating
- Reference standard development
- Standalone performance testing
- Clinical performance testing
- Data enrichment
- Emphasis on “explainability”
- Additional labeling requirements
Who Should Attend
- Software Engineers
- Regulatory Personnel
- Quality Assurance Personnel
Why Should You Attend
It is not clear how to get AI/ML programs approved. The current regulatory requirements don’t control AI/ML adequately. We will discuss the approaches FDA is considering for regulation in the near future and how to get your AI/ML program approved by the FDA now. Necessary submission documentation will be explained.
Attendees will receive a multipage outline and checklist.