Recap of the FDA and CTTI Public Workshop on AI in Drug Development

At a Glance

• Throughout the workshop, panelists repeatedly emphasized the need for clarity and explicit guidance from regulators around the use of AI in drug development.
• Panelists called on the FDA to develop guidance on data transparency and consider new product development pathways that may assist in increasing the amount of real-world performance data.
• Dr. Patrizia Cavazzoni, the director of the FDA’s Center for Drug Evaluation and Research (CDER), stated that the FDA is in the process of drafting risk-based guidance on the use of AI for drug development.

On August 6, 2024, the Food and Drug Administration (FDA) partnered with the Clinical Trials Transformation Initiative (CTTI) to hold a joint, public workshop titled, “Artificial Intelligence (AI) in Drug & Biological Product Development,” to discuss guiding principles for the responsible use of AI in the development of safe and effective drugs and biological products. The FDA announced this workshop in the Federal Register on July 10.

The full-day workshop included four panel sessions with speakers from the FDA, academia, drug sponsors, technology organizations and other industry members. The four sessions focused on optimizing model design through multidisciplinary expertise; exploring strategies for overcoming common-data related challenges and the availability of fit-for-use data for drug development; balancing model performance, explainability and transparency of AI models; and identifying key gaps and challenges hindering the use of AI in drug and biological product development.

Throughout the workshop, panelists repeatedly emphasized the need for clarity and explicit guidance from regulators around the use of AI in drug development. Some panelists also called for global regulators to work together to align and harmonize AI standards and best practices. Other issues the panelists focused on included the importance of having interdisciplinary collaboration to explore the benefits of AI in drug development, and the importance of the FDA highlighting even the small AI successes to educate and build trust around the use of AI. Panelists also encouraged stakeholders to embrace the use of AI, with one panelist suggesting the FDA create incentives for drug development industry members to integrate AI into their processes. Another issue discussed was the lack of available data to support the safe use of AI in drug development. Panelists called on the FDA to develop guidance on data transparency and consider new product development pathways that may assist in increasing the amount of real-world performance data.

Pharmaceutical companies are already examining ways to use AI in their drug development processes. For example, Genesis Therapeutics recently announced its third deal with major biopharma companies for the use of GEMS, a generative AI platform for drug discovery. But, as the workshop made clear, the industry needs resources, partnerships, clear guidance and standards from the FDA and other regulatory bodies, in the United States and globally, in order to further the use of AI in the drug development process. Dr. Patrizia Cavazzoni, the director of the FDA’s Center for Drug Evaluation and Research (CDER), stated that the FDA is in the process of drafting risk-based guidance on the use of AI for drug development. However, the timeline for the publication of this guidance is not clear.