Risk Management for AI in Medical Devices: Insights from FDA’s Life Cycle Management Draft Guidance

The FDA’s Total Product Life Cycle, or TPLC, approach to the oversight of AI in medical devices is discussed in their January 2025 Lifecycle Draft Guidance. The FDA’s TPLC approach allows the FDA to review and monitor medical devices throughout their life cycle by taking into account all available information on safety and effectiveness.  

FDA will take a risk-based approach to specific testing needs and applicable recommendations to support marketing submissions for AI-enabled devices. A “device software function” is a software function that meets the device definition in section 201(h) of the Federal Food, Drug, and Cosmetic Act (FD&C Act).  AI-enabled devices are devices that include one or more AI-enabled Device Software Functions (AI-DSFs). This guidance are intended to assist with device development and lifecycle management of AI-enabled devices, which should help support the safety and effectiveness of these devices.

This guidance provides both:

1. Specific recommendations on the information and documentation to support a marketing submission for an AI-enabled device, as well as
2. Recommendations for the design, development, deployment, maintenance of AI devices, including performance management.

This guidance also includes FDA’s current thinking on strategies to address transparency and bias throughout the TPLC of AI-enabled devices. These should be incorporated from device design through decommission to help design transparency and the control of bias into the device and ensure its safety and effectiveness. This webinar will provides recommendations on the documentation that should be included in marketing submissions (510(k)s, De Novos, PMAs, HDEs, BLAs) to support FDA’s review of devices that include AI-DSFs. 

WHY YOU SHOULD ATTEND:

This webinar will cover the FDA’s total product life cycle approach and FDA’s roles and responsibilities in regulating medical devices throughout their lifecycle. The US FDA has long promoted a Risk-Based Total Product Life Cycle (TPLC) approach to the oversight of medical devices, including artificial intelligence (AI)-enabled devices.  Some recent efforts include developing guiding principles for good machine learning practice (GMLP) and transparency for machine learning-enabled devices. This is to help promote safe, effective, and high-quality machine learning models.  They have held a public workshop on fostering a patient-centered approach to AI-enabled devices, including discussions of device transparency for users.

This webinar will examine the new January 2025 Draft Guidance on "Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management and Marketing Submission Recommendations" . This Guidance provides total lifecycle management and marketing submission recommendations consistent with a  TPLC approach for AI-enabled devices. This guidance provides recommendations on the contents of marketing submissions (510(k), De Novos, PMAs) for devices that include AI-enabled device software functions including documentation and information that will support FDA’s review.

AREAS COVERED:

• The New 2025 Draft Guidance  For AI-Enabled Medical Devices 
• What is Risk-Based?
• Total Product Life Cycle (TPLC) Approach to Medical Devices
• Specific FDA requirements for SI-DSF Submissions
• FDA Recommendations for the design, development, deployment, maintenance of AI devices
• Contents of marketing submissions (510(k)s, De Novos, PMAs, HDEs, BLAs) w/ AI-DSFs. 
• TPLC Considerations Pre- and Post-market and in Submissions/FDA Reviews

WHO SHOULD ATTEND:

• Quality Assurance Departments
• Regulatory Affairs Departments
• AI Software Programming, Documentation, Testing Teams
• Research and Development Departments
• Engineering Departments
• Production Departments
• Operations Departments
• Senior Management
• Consultants; others tasked with IVD product projects

Course Director: JOHN E. LINCOLN  

John E. Lincoln, is Principal of J. E. Lincoln and Associates LLC, a consulting company with over 36 years experience in U.S. FDA-regulated industries, 22 of which are as an independent consultant. John has worked with companies from start-up to Fortune 100, in the U.S., Mexico, Canada, France, Germany, Sweden, China and Taiwan. He specializes in quality assurance, regulatory affairs, QMS problem remediation and FDA responses, new / changed product 510(k)s, process / product / equipment QMS and software validations, ISO 14971 product risk management files / reports, Design Control / Design History Files, Technical Files, CAPA systems and analysis. He’s held positions in Manufacturing Engineering, QA, QAE, Regulatory Affairs, to the level of Director and VP (R&D). In addition, John has prior experience in military, government, electronics, and aerospace. He has published numerous articles in peer reviewed journals, conducted workshops and webinars worldwide on CAPA, 510(k)s, risk analysis / management, FDA / GMP audits, validation, root cause analysis, and others. He writes a recurring column for the Journal of Validation Technology. John is a graduate of UCLA.