FDA Explores AI to Accelerate Drug Approval Process with OpenAI

The Food and Drug Administration (FDA) is exploring the use of artificial intelligence (AI) to streamline its drug approval process, a move that could significantly reduce the time it takes for new medications to reach patients. According to sources familiar with the situation, the FDA has been in discussions with OpenAI, a leading AI research lab, as part of this initiative.

The potential impact on public health is significant. Currently, it can take over 10 years for a new drug to move from the laboratory to the pharmacy shelf, a timeline that many find unacceptably long. In a recent post on X (formerly Twitter), FDA Commissioner Marty Makary highlighted these delays and called for modernization with AI.

"Why does it take over 10 years for a new drug to come to market?" Makary wrote. "Why are we not modernized with AI and other things? We’ve just completed our first AI-assisted scientific review for a product, and that’s just the beginning."

Makary's remarks followed an annual meeting of the American Hospital Association, where he discussed how AI could aid in the approval of new treatments for conditions like diabetes and certain types of cancer. While Makary did not specify OpenAI's involvement, sources close to the project confirm that a small team from OpenAI has met with FDA officials multiple times in recent weeks. These meetings also included representatives from Elon Musk’s so-called Department of Government Efficiency.

One key project under discussion is cderGPT, which likely stands for "Center for Drug Evaluation and Research GPT." The Center for Drug Evaluation and Research (CDER) is the branch of the FDA responsible for regulating over-the-counter and prescription drugs in the United States. Jeremy Walsh, recently appointed as the FDA’s first AI officer, has been leading these discussions. To date, no formal contract has been signed.

Walsh has also met with Peter Bowman-Davis, an undergraduate on leave from Yale University who currently serves as the acting chief AI officer at the Department of Health and Human Services (HHS). The appointment of Bowman-Davis, first reported by Politico, has raised some eyebrows due to his young age and lack of extensive experience in government. However, he is part of Andreessen Horowitz’s American Dynamism team, a group focused on advancing technology and innovation in public sectors.

The use of AI in drug approval processes is not entirely new. Robert Califf, who served as FDA commissioner from 2016 to 2017 and again from 2022 through January, noted that the agency has been using AI for several years. "It will be interesting to hear the details of which parts of the review were 'AI assisted' and what that means," Califf said via email. "There has always been a quest to shorten review times, and there is a broad consensus that AI could help."

Califf added that while final reviews for drug approval are crucial, they represent only one aspect of a larger opportunity. Before his departure from the agency, he emphasized that the FDA was considering various ways AI could be integrated into its internal operations.

The potential benefits of using AI in this context are substantial. AI can analyze vast amounts of data more quickly and accurately than human reviewers, potentially identifying patterns and risks that might otherwise go unnoticed. This could lead to faster and more thorough evaluations, ultimately bringing new treatments to patients sooner.

However, there are also concerns about the reliability and transparency of AI systems in such critical processes. Ensuring that these technologies are robust, unbiased, and explainable will be essential for maintaining public trust and regulatory integrity.

As the FDA continues to explore the use of AI, it is clear that this technology has the potential to revolutionize how new drugs are evaluated and approved. The coming months will likely bring more details on how cderGPT and other AI tools will be integrated into the agency's operations, with the ultimate goal of improving public health outcomes.