The US Food and Drug Administration (FDA) has unveiled Elsa, a secure generative AI platform developed in-house to support its employees in streamlining tasks such as protocol review, label comparisons, and internal data analysis. The launch, which comes ahead of schedule and under budget, marks a significant step in the agency’s broader digital transformation.

Elsa—short for “Enterprise-level secure assistant”—is designed to help FDA staff across departments, including scientific reviewers, investigators and inspectors, to complete complex tasks faster while protecting sensitive data.

“Following a very successful pilot program with FDA’s scientific reviewers, I set an aggressive timeline to scale AI agency-wide by June 30,” said FDA commissioner Marty Makary. “Today’s rollout of Elsa is ahead of schedule and under budget, thanks to the collaboration of our in-house experts across the centers.”

The tool is hosted within a high-security GovCloud environment, ensuring all data remains internal to the FDA. It does not train on any information submitted by regulated industry, maintaining the confidentiality of proprietary research and regulatory data.

Elsa is already being used to speed up clinical protocol reviews, identify high-priority inspection targets, and reduce the time required for scientific evaluations. The AI platform can also summarise adverse event reports, generate database code, and assist with safety profile assessments and nonclinical data workflows.

“Today marks the dawn of the AI era at the FDA with the release of Elsa,” said FDA chief AI officer Jeremy Walsh. “AI is no longer a distant promise but a dynamic force enhancing and optimizing the performance and potential of every employee. As we learn how employees are using the tool, our development team will be able to add capabilities and grow with the needs of employees and the agency.”

Elsa’s deployment is part of a wider push by the FDA to embed artificial intelligence throughout its regulatory and operational functions. Further integration is expected as the agency explores additional use cases such as advanced data processing and expanded generative-AI applications.

By prioritising both efficiency and responsibility, the FDA is positioning itself at the forefront of AI adoption in regulatory science, taking a measured but ambitious approach to future development.