Congress should invest in AI and data science training to prepare the next generation of scientists for AI-supported drug development by integrating AI into biomedical research, supporting cross-disciplinary collaboration, and establishing best practices.

To Do: Invest in AI and Data Science Training for Drug Development

Congress should pass the Privacy Enhancing Technology Research Act mandating NSF to support research into privacy-enhancing technologies and directing OSTP to coordinate efforts with other federal agencies to accelerate the technologies’ development, deployment, and adoption.

To Do: Pass the Privacy Enhancing Technology Research Act

The White House’s AI Action Plan highlights how upgrading labs, data infrastructure, and research models is essential to unlock AI’s full potential in accelerating drug discovery and keeping the United States at the forefront of biopharmaceutical innovation.

America’s AI Action Plan: Implications for Biopharmaceutical Innovation

America's AI Action Plan: Implications for Biopharmaceutical Innovation

Congress should fund NIH’s “All of Us” research program to improve the representativeness of datasets used in biomedical research.

To Do: Improve the Datasets Needed for Biomedical Research

Sandra Barbosu chairs a session about AI and pharmaceuticals at the 2025 BioTechX conference.

AI in Drug Discovery and Development 

Congress should fund and direct the National Science Foundation (NSF) to create a competitive AI fellowship program for at least 1,000 computer science students annually.

To Do: Expand Investments in AI Talent

The administration should develop a national AI roadmap that outlines sector-specific opportunities and barriers, as well as a detailed strategy for achieving widespread adoption in each of these sectors.

To Do: Create a National Roadmap for AI Adoption

The White House should direct federal agencies to develop sector-specific AI strategies to spur AI adoption and development in industry.

To Do: Develop Sector-Specific AI Strategies

AI can reduce the time it takes to synthesize and screen new drugs by 40 percent to 50 percent, reducing costs in those parts of the research process by as much as $26 billion annually.

To Do: Accelerate AI Adoption in Biopharma Research

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Editors’ Recommendations

Harnessing AI to Accelerate Innovation in the Biopharmaceutical Industry

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To Do: Invest in AI and Data Science Training for Drug Development

To Do: Pass the Privacy Enhancing Technology Research Act

America’s AI Action Plan: Implications for Biopharmaceutical Innovation