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Leveraging Artificial Intelligence in Drug and Biological Product Development: An FDA and Clinical Trial
Atasi Poddar1, Marsha Samson1, Gabriel K Innes1
1Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
NEJM AI
|December 12, 2025
Summary
Artificial intelligence (AI) can significantly improve drug development efficiency. This article discusses challenges and policy needs for AI integration in drug and biological product development.
Area of Science:
- Pharmacology and Pharmaceutical Sciences
- Biotechnology
- Regulatory Science
Background:
- Artificial intelligence (AI) presents opportunities to enhance efficiency and accuracy in drug development.
- Scalable adoption of AI in drug development faces unique challenges.
- Regulatory bodies and industry stakeholders are exploring AI's role.
Purpose of the Study:
- To synthesize insights from a public workshop on AI in drug and biological product development.
- To identify guiding principles for AI implementation in the pharmaceutical sector.
- To highlight the need for policy development to support AI integration.
Main Methods:
- A public workshop was convened by the U.S. Food and Drug Administration and the Clinical Trial Transformation Initiative.
- Participants included medical product sponsors, technology innovators, academicians, and regulators.
- Key insights from discussions on AI's application and challenges were synthesized.
Main Results:
- AI has transformative potential across the drug product lifecycle.
- Discussions identified key principles for responsible AI use.
- Emerging challenges to scalable AI adoption were highlighted.
Conclusions:
- Policy development is crucial for enhancing AI integration in drug and biological product development.
- Collaboration between regulators, industry, and academia is essential.
- Realizing AI's full potential requires addressing current challenges and establishing clear guidelines.
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