This interactive session will explore the rapidly evolving landscape of FDA regulations, focusing on thorny issues such as continuous learning systems, the integration of large language models (LLMs), and the debate between lab-developed tests and commercial vendor solutions. Participants will engage in point-counter-point discussion, utilize a whiteboard for collaborative brainstorming, and contrast current regulatory approaches with potential future needs. This session aims to empower attendees with insights into the challenges and opportunities of navigating FDA regulations in AI and healthcare technology.

Objectives

• Discuss the implications of continuous learning and LLM integration on FDA regulatory frameworks.
• Compare lab-developed tests with vendor/commercial solutions in the context of regulatory challenges.
• Identify actionable steps to address gaps in current FDA approaches for AI technologies.