EMA, FDA issue joint AI guiding principles for drug developers

The European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) have issued a joint list of guiding principles of good artificial intelligence (AI) practices when using the technology to develop drugs. Key considerations of the principles include taking a risk-based total product lifecycle approach and adhering to updated AI standards.

On 14 January, FDA and EMA listed 10 guiding principles that drug sponsors should consider as they use AI in their product development. The regulators noted that the use of AI technology throughout the product lifecycle has significantly increased in recent years and could be beneficial if used properly.

"Among other innovations, AI technologies are anticipated to support a multi-faceted approach that promotes innovation, reduces time-to-market, strengthens regulatory excellence and pharmacovigilance, and decreases reliance on animal testing by improving the prediction of toxicity and efficacy in humans," said the regulators. "This document outlines a common set of principles to inform, enhance, and promote the use of AI for generating evidence across all phases of the drug product life cycle.

"The 10 guiding principles identify areas where the international regulators, international standards organizations, and other collaborative bodies could work to advance good practice in drug development," they added. "Areas of collaboration include research, creating educational tools and resources, international harmonization, and consensus standards, which may help inform regulatory policies and regulatory guidelines in different jurisdictions, in line with applicable legal and regulatory frameworks."

Joe Franklin, special counsel at Convington & Burling, said the document is helpful in guiding manufacturers as they consider using AI technology.

“The new document affirms both the anticipated benefits of AI in drug development as well as many of the AI deployment considerations that companies are building into AI governance,” he told Focus.

The guiding principles include ensuring the AI is designed based on ethical and human-centric values; uses a risk-based approach that factors in validation, risk mitigation, and oversight based on the context of use; and adheres to relevant legal, scientific, regulatory, and other standards. They also include ensuring the technology is used in a clear context and is developed using multidisciplinary expertise.

"As the use of AI in drug development evolves, so too must good practice and consensus standards," regulators said. "Strong partnerships with international public health partners will be crucial to empower stakeholders to advance responsible innovations in this area.

"Thus, this initial collaborative work can inform our broader international engagements," they added.

The regulators also emphasized the need for good data governance and documentation when using AI technology, which they stated should be based on best practices in model and system design, as well as software engineering. Furthermore, they said that they should be evaluated using a risk-based performance assessment, adopt a lifecycle management approach, and present essential information in plain language.

The guiding principles are reminiscent of the good machine learning practices (GMLP) guiding principles adopted by regulators in the US, UK, and Canada, as well as the International Medical Device Regulators Forum (IMDRF) over the past few years. (RELATED: IMDRF finalizes good machine learning practice, software risk documents, Regulatory Focus, 29 January 2025)

AI guiding principles

EMA, FDA issue joint AI guiding principles for drug developers

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