ArticleClinical pharmacology and therapeutics2026
Regulatory Research Priorities for AI Use in the Medicine Lifecycle: A European Perspective with Global Relevance.
Article in Clinical pharmacology and therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Regulatory bodies play a central role in providing guidance that enables safe and effective use of artificial intelligence tools in medicine development and evaluation. Regulators can also act as catalysts for regulatory science research. To inform these efforts, a European-wide survey was conducted to solicit stakeholder perspectives on the priority areas for regulatory science research related to the use of artificial intelligence in the medicine lifecycle. Twenty-eight regulatory science research questions were developed covering seven thematic domains: (1) research integrity and intellectual property; (2) accuracy and reliability of AI tools; (3) data governance, confidentiality, and consent; (4) regulation and oversight; (5) ethics, fairness, and bias prevention; (6) resources and support for AI use; and (7) impact on jobs and skills. Within each domain, stakeholders ranked four research challenges. A total of 273 responses were collected from regulators, pharmaceutical industry professionals, patients and consumers, academics, and healthcare professionals. Rankings of research challenges frequently converged across stakeholder groups and levels of AI experience. The top-ranked research questions within each domain were weighted according to the overall importance ranking of each domain to identify a list of 10 priority areas of research. The majority of the 10 priority areas fell within the domains of "Accuracy and reliability of AI tools," "Data governance, confidentiality, and consent," and "Ethics, fairness, and bias prevention." This list aims to support researchers and research funding bodies in addressing knowledge gaps on artificial intelligence in the medicines lifecycle.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.