Artificial Intelligence for Regulatory Evidence: A Systematic Document Analysis of European Medicines Agency Regulatory Advice and Public Reports

Abstract

Artificial intelligence (AI) is receiving increasing attention across the entire lifecycle of medicines, from early development to postauthorization use. While various AI tools have been developed in commercial and academic settings, the extent of their use in regulatory contexts within the European Union remains unknown. In this study, we systematically analyzed the use of AI for regulatory evidence by reviewing Public reports and internal development advice documents from the European Medicines Agency (EMA). Of 26,480 documents screened, 52 documents contained AI use, reflecting 43 unique AI tools used across quality, nonclinical, clinical, and pharmacovigilance domains. The majority of AI tools were deployed in clinical applications, and outputs were used either directly as endpoints, in shaping clinical trial methodology, or in ancillary analyses. Comments and advice from the EMA regarding AI use varied according to the context of use and covered aspects of documentation, methodology, validation, and lifecycle management. Our findings indicate that AI use in regulatory evidence is still limited but showing an increasing trend. As the field is still novel, there are limited regulatory precedents, and AI-specific guideline development and harmonization across regulatory jurisdictions are still ongoing. In this light, the quantitative characterization of AI tools and AI-related regulatory comments captured in this analysis provide concrete insights into AI use and frequent regulatory considerations, aiding in both AI tool and AI guideline development.