Overview
The use of Generitive AI in the Drug Development Process. The US FDA's encouragement of AI technology in pharma development and clinicals.
The US FDA has announced steps toward a new regulatory policy specifically tailored to promote the development of safe and effective drugs using advanced artificial intelligence / machine learning algorithms by the regulated industry. Artificial intelligence algorithms are software that can learn from and act on data. These types of algorithms are already being used on a limited but growing scale by industry to aid in screening for diseases and to provide treatment recommendations. The recent FDA authorizations of medical devices and their drug development policy statements indicate these technologies are viewed as a harbinger of progress that the FDA expects to seein the five basic ements of drug development: 1) Discovery and development, 2) Preclinical research, 3) Clinical research, 4) FDA review, and 5) FDA post-marketing safety monitoring. AI production software validation has some new requirements as well. The Agency plans to apply their current authorities in new ways to keep up with the rapid pace of innovation and ensure the safety of these drugs. This seminar will evalusate these stated FDA policy shifts as it applies to drug development.
Why Should You Attend
Generative AI is a type of artificial intelligence (AI) that attempts to match or surpass human thinking abilities across a wide range of large data tasks. The FDA is adapting to the use of AI in medical products, and has recently issued policy statements on an advanced form of AI in pharma development, looking to the future. One of these is AIRIS. AIRIS operates without pre-set commands or training data, solving problems and creating rules as it navigates the virtual world. In artificial intelligence (AI), creating adaptable systems that learn independently is a key goal, and AIRIS (Autonomous Intelligent Reinforcement Inferred Symbolism) is an AI system designed to do just that. It is enabled to adapt and solve problems in new situations without needing explicit programming for each task. While FDA specifically mentions AIRIS, their statements indicate a williness to work with their regulated industry partners in expanding use of generative AI into all appropriate areas of pharmaceutical development, production, and post market monitoring.
Agenda
- Generative AI
- AIRIS example
- The Drug Development Process - 5 Key Steps and AI
- The US FDA Commissioner's Comments
- Discovery and Development
- Preclinical Research
- Clinical Research
- FDA Review
- Post-market Safety Monitoring / Reporting
- Patient Focused Development
Who Will Benefit
- Senior management in Pharmaceuticals
- QA / RA
- AI software programming, documentation, testing teams
- R&D
- Engineering
- Production
- Operations
- Marketing
- Consultants; others tasked with pharmaceutical development responsibilities
Faculty John E Lincoln
Principal, J E Lincoln and Associates
John E. Lincoln, is Principal of J. E. Lincoln and Associates LLC, a consulting company with over 41 years experience in U.S. FDA-regulated industries, 27 years as head of his own consulting company. 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 including QMS and software validations, ISO 14971 product risk management files / reports, Design Control / Design History Files, Technical Files. 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, 5 chapters in the RAPS textbook on validation, conducted workshops and webinars worldwide on CGMP subjects. John is a graduate of UCLA.
