Litcius/Paper detail

Artificial intelligence integration in the drug lifecycle and in regulatory science: policy implications, challenges and opportunities

Wahiba Oualikene-Gonin, Marie‐Christine Jaulent, Jean-Pierre Thierry, Sofia Oliveira‐Martins, Laëtitia Belgodère, Patrick Maison, Joël Ankri, The Scientific Advisory Board of ANSM

2024Frontiers in Pharmacology37 citationsDOIOpen Access PDF

Abstract

Artificial intelligence tools promise transformative impacts in drug development. Regulatory agencies face challenges in integrating AI while ensuring reliability and safety in clinical trial approvals, drug marketing authorizations, and post-market surveillance. Incorporating these technologies into the existing regulatory framework and agency practices poses notable challenges, particularly in evaluating the data and models employed for these purposes. Rapid adaptation of regulations and internal processes is essential for agencies to keep pace with innovation, though achieving this requires collective stakeholder collaboration. This article thus delves into the need for adaptations of regulations throughout the drug development lifecycle, as well as the utilization of AI within internal processes of medicine agencies.

Topics & Concepts

Regulatory scienceBusinessTransformative learningPaceAgency (philosophy)Drug developmentStakeholderAdaptation (eye)Knowledge managementProcess managementRisk analysis (engineering)Computer scienceDrugMedicinePolitical sciencePublic relationsPharmacologyOpticsPhysicsPhilosophyEpistemologyPathologyGeodesyPsychologyPedagogyGeographyBiosimilars and Bioanalytical MethodsEthics in Clinical ResearchBiomedical Ethics and Regulation