Artificial intelligence is here to stay at the FDA, but its path forward looks less certain after the departure of a major proponent. Former commissioner Marty Makary stepped down recently, leaving questions about the agency’s centralized approach to the technology. Makary was pushing for a unified strategy, rolling out an agency-wide tool called Elsa to accelerate reviews by handling support tasks like summarizing reports.
Between 2024 and 2025, the number of AI use-cases reported by the FDA skyrocketed by 148% amid a broader government push to leverage the tech, according to a Bipartisan Policy Center study. This rapid adoption highlights how deeply the technology has penetrated daily operations.
Acting commissioner Kyle Diamantas said AI remains a top priority for the FDA. Still, recent high-level departures, including Makary, Jeremy Walsh, chief artificial intelligence officer, and Sridhar Mantha, acting chief information officer, have raised questions about the future of AI implementation.
“It’s unclear now what the leadership and governance structure are around FDA-wide efforts,” said Tala Fakhouri, chief artificial intelligence and regulatory strategy officer at Parexel, and a former FDA AI policy official.
Leadership Vacuum Raises Questions
FDA officials have spoken about AI at recent conferences, but they were all representing individual divisions, Fakhouri said. She noted that this could portend a return to the more fragmented, department-specific AI approach that existed prior. At the same time, efforts to increase transparency around AI use and enact AI-related policy-making could also slow.
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These potential setbacks primarily concern the agency’s internal use of AI, and not those governing how drug companies apply the technology in their own work. So far, there hasn’t been a change in the FDA’s policies as they relate to the sponsor use of AI.
“And I don’t expect to see a change there, which is good,” Fakhouri said.
Internal Tools Like Elsa Face Uncertainty
FDA’s internal use of AI to streamline staff workloads has evolved steadily in recent years. Elsa had its origins in a CDER-developed program, CDER GPT. The agency expanded on that original program to use a retrieval-augmented generation system to reduce AI hallucinations.
The system is designed to confine the large language model to a well-defined database of trusted information, tailored for the individual centers within the agency. This allows staff to use the tool to access information needed for their unique roles. For example, staff members can quickly generate a summary of industry comments on a particular proposal.
The agency now faces a difficult balancing act. It must maintain the momentum gained during the centralized push while simultaneously rebuilding its leadership bench. If the governance gap widens, the efficiency gains seen with tools like Elsa could stall just as they were beginning to scale effectively.
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While Elsa has been leveraged for these types of burdensome tasks, Fakhouri doesn’t believe the technology is used for final decision-making.
“Staff can use the tools to augment the work that they’re doing. We should all be happy about that,” she said.
The Push for Transparency
Transparency about how the FDA is using AI in its processes is still lacking, Fakhouri said.
“If the regulators are using AI in certain ways to augment reviewer work or to become an assistant to a reviewer, I think it’s good practice for industry to know what these uses look like,” she said.
Fakhouri said that detailing how the FDA is using AI could help collaboration with the industry. She suggested that if sponsors knew how the AI assistant worked, they could prepare their submissions with data labels and information helpful for the reviewer.
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Fakhouri said she expects the agency to move toward greater transparency over time. “But it would require someone in a leadership position at the agency to become aware of that and want to actually make it happen,” she added.
Fakhouri would also like to see the agency streamline AI-related rulemaking that impacts the industry, such as how AI tools are validated for clinical trials. Under Makary, policy changes were sometimes announced outside the traditional FDA guidance process and through journal articles or press conferences instead.
The agency appears to be returning to its former norms under Diamantas, who recently confirmed that informal statements made by the former commissioner don’t represent official policy.
“They will go through the regular guidance and policy development processes,” Fakhouri said.
While traditional rulemaking insulates pharma from uncertainty, it can also be a slower process that creates its own challenges as companies rapidly adopt different AI platforms.
