In January 2026, the U.S. Food and Drug Administration (FDA), through its Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER), jointly published with the European Medicines Agency (EMA) a set of ten guiding principles for the use of artificial intelligence (AI) in drug and biological product development. The document is final and published; it carries no binding legal force as a regulation but constitutes authoritative guidance from two of the world's leading medicines regulators.
The ten principles address the full AI development life cycle as applied to drug development. They require AI systems to be human-centric by design and to adopt a risk-based approach calibrated to the specific use case. Principle 3 calls for adherence to applicable regulatory standards. Principle 4 demands clarity on the context of use, meaning developers must precisely define the intended purpose of each AI model. Further principles require multidisciplinary expertise from cross-functional teams, robust data governance and documentation, rigorous model design and development practices, and risk-based performance assessment. Principles 9 and 10 impose life cycle management obligations and prescribe that AI systems produce clear, essential information for regulatory review. The document was issued under FDA's general authority to issue guidance for regulated industry and reflects EMA's mandate under Regulation (EU) 2017/745 and related pharmaceutical legislation.
Drug and biological product developers using AI for any stage of the development cycle, nonclinical studies, clinical trials, manufacturing, or regulatory submissions, should map their existing practices against all ten principles. FDA noted that CDER has received more than 500 submissions with AI components from 2016 to 2023, indicating that agencies will scrutinize AI methodology as a standard part of regulatory review. Developers submitting AI-generated data to either agency should document model design, training data provenance, and validation procedures consistent with Principles 6 through 8.
The guiding principles do not create a new approval requirement or preempt existing regulations. They supplement FDA's January 2025 draft guidance "Considerations for the Use of Artificial Intelligence to Support Regulatory Decision Making for Drug and Biological Products" and sit alongside ongoing FDA and EMA work on AI in medical devices and clinical trials. Developers should note that these principles represent current agency thinking and may be superseded or elaborated by final guidances, policy statements, or legislation in either jurisdiction.
Our firm advises pharmaceutical, biotechnology, and medical technology companies on regulatory compliance in the United States and European Union, and maintains a dedicated partnership network for cross-border matters. We welcome inquiries on matters related to AI in drug development, FDA regulatory submissions, EMA regulatory strategy, AI governance frameworks, and pharmaceutical regulatory compliance.
Source: U.S. Food and Drug Administration, CDER/CBER and EMA, "Guiding Principles of Good AI Practice in Drug Development," January 2026, https://www.fda.gov/about-fda/artificial-intelligence-drug-development/guiding-principles-good-ai-practice-drug-development.
The information provided is not legal, tax, investment, or accounting advice and should not be used as such. It is for discussion purposes only. Seek guidance from your own legal counsel and advisors on any matters. The views presented are those of the author and not any other individual or organization. Some parts of the text may be automatically generated. The author of this material makes no guarantees or warranties about the accuracy or completeness of the information.