FDA Issues New Recommendations for Use of Artificial Intelligence to Support Regulatory Actions

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The FDA has issued a draft guidance outlining recommendations for the use of artificial intelligence (AI) to support regulatory decisions regarding the safety, efficacy, or quality of drugs and biological products. According to the regulatory agency, this marks its first guidance on AI applications in drug and biological product development.¹

“The FDA is committed to supporting innovative approaches for the development of medical products by providing an agile, risk-based framework that promotes innovation and ensures the agency’s robust scientific and regulatory standards are met,” said Robert M. Califf, MD, Commissioner, FDA, in a press release. “With the appropriate safeguards in place, artificial intelligence has transformative potential to advance clinical research and accelerate medical product development to improve patient care.”

The FDA stated that the new guidelines will work to define the context of use—the specific application of an AI model—and assessing its credibility for that purpose, aligning with the agency’s experience in evaluating over 500 submissions involving AI components since 2016. Currently, AI applications are being used in predicting patient outcomes, understanding disease progression, and analyzing complex datasets. As a result, the FDA suggests that all regulatory evaluations should ensure model credibility—trust in the performance of an AI model for a particular context of use.¹

At last year’s Financial Times US Pharma and Biotech Summit, Pharmaceutical Executive interviewed Tala Fakhouri, FDA associate director for Policy Analysis, to discuss the use of AI as well as machine learning through the eyes of the regulatory body.²

“For the FDA, our approach is always risk-based for drug approvals. We also do our best to be responsive to new emerging technologies,” said Fakhouri. “This is not just for AI if you think about the use of real-world data, or the use of digital health technologies in clinical research. In the context of a clinical trial, these are all emerging technologies that are continuously evolving. We plan to grow with all of these emerging tools as they become available.”

As previously alluded to, Fakhouri also spoke about the high number of submissions that have included AI since 2016.

“Like I said, we’ve received over 300 submissions with AI and machine learning components. Depending on the specific context of the risk associated with using that model, how much am I relying on information or data from that model to make a regulatory decision? All of these would drive the type of information that we would ask the sponsor to provide us with,” Fakhouri continued.

Back in October, the FDA released updated guidelines on the use of AI for drug development, stating that it understands the growing role of AI in drug development, spanning the entire drug lifecycle from nonclinical and clinical phases to manufacturing and post marketing. Earlier in the year, the Center for Drug Evaluation and Research (CDER) released a draft guidance addressing AI’s use in regulatory decision-making. As a result, the FDA guidelines are influenced by extensive public feedback, CDER’s review of over 500 AI-related submissions since 2016, workshops with stakeholders, and aligns with broader FDA efforts to ensure responsible AI use.³

Moving forward, the FDA encourages sponsors to engage early to ensure their AI models meet the required credibility standards. Alongside the draft, the agency also issued recommendations specific to AI-enabled medical devices, reinforcing its commitment to ethical and responsible AI use while maintaining robust safety and effectiveness standards.¹

References

1. FDA Proposes Framework to Advance Credibility of AI Models Used for Drug and Biological Product Submissions. FDA. January 6, 2025. Accessed January 6, 2025. https://www.fda.gov/news-events/press-announcements/fda-proposes-framework-advance-credibility-ai-models-used-drug-and-biological-product-submissions

2. US Pharma and Biotech Summit 2024: Artificial Intelligence and Machine Learning Through the Eyes of the FDA. PharmExec. May 16, 2024. Accessed January 6, 2025. https://www.pharmexec.com/view/us-pharma-and-biotech-summit-2024-artificial-intelligence-machine-learning-through-eyes-fda

3. Artificial Intelligence for Drug Development. FDA. October 31, 2024. Accessed January 6, 2025. https://www.fda.gov/about-fda/center-drug-evaluation-and-research-cder/artificial-intelligence-drug-development