Generative AI refers to a class of artificial intelligence technologies designed to perform complex data-driven tasks in ways that increasingly resemble, and in some cases may exceed, human analytical capabilities. The FDA is actively responding to the expanding role of AI in medical product development and has recently shared policy perspectives on sophisticated AI applications in pharmaceutical research, with an eye toward future innovation. One example referenced in this context is AIRIS. AIRIS functions without relying on fixed instructions or preloaded training datasets, instead learning to address challenges and establish its own operating rules while interacting with a virtual environment. A central objective in AI is to build systems that can independently adapt, and AIRIS, or Autonomous Intelligent Reinforcement Inferred Symbolism, was developed with that goal in mind. It is intended to respond to unfamiliar situations and resolve problems without requiring task-by-task programming. Although the FDA specifically cites AIRIS, its broader comments also reflect the Agency’s overall direction on AI use in drug discovery and development, along with its openness to collaborating with regulated companies to expand generative AI across suitable areas of pharmaceutical research, manufacturing, and post-market oversight.
The application of Generative AI throughout the drug discovery and development lifecycle. The U.S. FDA supports AI innovation in pharmaceutical development and clinical research through a risk-based regulatory approach.
Areas Covered in the Session:-
Why Should You Attend?
The U.S. FDA has signaled movement toward a revised regulatory policy and framework aimed at supporting the creation of safe and effective drug products developed with advanced artificial intelligence and machine learning technologies by regulated organizations. AI-based algorithms are software systems capable of learning from data and taking action based on those insights. These technologies are already being adopted by industry on an expanding, though still limited, basis for activities such as disease screening and treatment guidance. Recent FDA clearances for medical devices, together with public policy statements related to drug development, suggest the Agency sees these tools as an important indicator of future advancement across the five fundamental stages of drug development: 1) Discovery and development, 2) Preclinical research, 3) Clinical research, 4) FDA review, and 5) FDA post-marketing safety monitoring. Validation expectations for AI-driven production software are also evolving with added requirements. The FDA intends to use its existing authorities in updated ways to address the speed of technological progress while continuing to safeguard product safety and effectiveness. This seminar will examine these emerging FDA policy directions and their impact on drug discovery and development activities.
Who Should Attend?
John E. Lincoln is the Principal of J. E. Lincoln and Associates, a consulting company with over 41 years of experience in U.S. FDA-regulated industries, 27 of which as head of his own consulting company. John has worked with companies from start-ups 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, FDA responses, new/changed product 510(k)s, process/product/equipment incl+D33uding QMS and software validations, ISO 14971 product risk management files/reports, Design Control / Design History Files, Technical Files. He's held Manufacturing Engineering, QA, QAE, and Regulatory Affairs positions at the Director and VP (R&D) levels. In addition, John has prior experience in the military, government, electronics, and aerospace. He has published numerous articles in peer-reviewed journals, including 5 chapters in the RAPs validation textbook, and conducted workshops and webinars worldwide on regulatory issues. John is a graduate of UCLA.
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