WASHINGTON, D.C. — The U.S. Food and Drug Administration (FDA) has unveiled a historic initiative to implement artificial intelligence (AI) technologies agency-wide, with a target completion date of June 30, 2025. The move marks a significant step toward leveraging AI capabilities to accelerate scientific reviews and optimize processes across all FDA centers.
FDA Commissioner Martin A. Makary, M.D., M.P.H., emphasized the agency’s commitment to reducing inefficiencies in critical workflows while maintaining high standards for public health oversight. “I was blown away by the success of our first AI-assisted scientific review pilot,” said Dr. Makary. “We need to value our scientists’ time and reduce the amount of non-productive busywork that has historically consumed much of the review process. The agency-wide deployment of these capabilities holds tremendous promise in accelerating the review time for new therapies.”
Transforming the Review Process
The FDA’s initiative is spurred by the success of a generative AI pilot program designed to support scientific reviewers. The tools used in this program have demonstrated their ability to handle repetitive, time-consuming tasks with remarkable efficiency. Jinzhong (Jin) Liu, Deputy Director of the Office of Drug Evaluation Sciences in the FDA’s Center for Drug Evaluation and Research (CDER), highlighted the impact of the technology, stating, “This is a game-changer technology that has enabled me to perform scientific review tasks in minutes that used to take three days.”
The generative AI system will allow scientists and subject-matter experts to allocate more time to high-priority analytical work, advancing the FDA’s mission to ensure public health through timely evaluations of new therapies and medical advancements.
Accelerated Timelines and Deployment
Dr. Makary has set an ambitious timeline, directing all FDA centers to begin AI deployment immediately, with full-scale integration planned by June 30, 2025. This effort includes adopting a secure, unified generative AI platform integrated with the FDA’s existing internal data systems.
To oversee the process, the FDA has appointed Jeremy Walsh, the agency’s new Chief AI Officer, to lead the rollout alongside Sridhar Mantha, formerly of CDER’s Office of Business Informatics. Walsh brings extensive experience in large-scale technology deployments within federal health and intelligence agencies.
The FDA leadership is aiming not only to expand AI applications but also to refine the technology for usability, security, and compliance with FDA policies. “There have been years of talk about AI capabilities in frameworks, conferences and panels but we cannot afford to keep talking,” said Dr. Makary. “It is time to take action. The opportunity to reduce tasks that once took days to just minutes is too important to delay.”
Next Steps and Future Enhancements
The agency will prioritize gathering user feedback and monitoring system performance during the rollout, ensuring the tool continues to meet the evolving needs of FDA staff. Future enhancements will focus on improving usability, expanding the range of documents the system can integrate, and tailoring outputs to the specific requirements of each FDA center.
Strict compliance with information security protocols will remain a key priority throughout implementation to safeguard data integrity and confidentiality. The FDA also intends to provide ongoing updates regarding the rollout, with additional details expected in June 2025.
Looking Ahead
The FDA’s full-scale adoption of AI technology represents a leap forward in regulatory oversight. By transforming its internal processes, the agency aims to accelerate the review of critical therapies and medical products, ultimately ensuring timely access for patients and contributing to advancements in public health.
With this initiative, the FDA is setting a precedent for how federal agencies can harness emerging technologies to enhance efficiency and maintain excellence. As implementation progresses, the agency’s forward-thinking approach may serve as a model for maximizing innovation in public service.
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