Skip to main content

PERSPECTIVE article

Front. Pharmacol.
Sec. Translational Pharmacology
Volume 15 - 2024 | doi: 10.3389/fphar.2024.1437167

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

Provisionally accepted
Wahiba OUALIKENE-GONIN Wahiba OUALIKENE-GONIN 1*Marie-Christine Jaulent Marie-Christine Jaulent 2,3Jean-Pierre Thierry Jean-Pierre Thierry 4Sofia Oliveira- Martins Sofia Oliveira- Martins 5Laetitia BELGODERE Laetitia BELGODERE 1Patrick Maison Patrick Maison 1,6,7Joel Ankri Joel Ankri 8,9
  • 1 Agence Nationale de Sécurité du Médicament et Des Produits de Santé (ANSM), Paris, France
  • 2 Institut National de la Santé et de la Recherche Médicale (INSERM), Paris, Île-de-France, France
  • 3 INSERM U1142 Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, Île-de-France, France
  • 4 France Assoc Santé, France / Paris, France
  • 5 Faculty of Pharmacy for Research and Development, University of Lisbon, Lisboa, Lisbon, Portugal
  • 6 EA7379 Epidémiologie en Dermatologie et évaluation des Thérapeutiques, Université Paris-Est Créteil, Créteil, France
  • 7 Hospital Center Intercommunal De Créteil, Créteil, France
  • 8 INSERM U1018 Centre de Recherche en Épidémiologie et Santé des Populations (CESP), Villejuif, Île-de-France, France
  • 9 Université de Versailles Saint-Quentin-en-Yvelines, Versailles, Île-de-France, France

The final, formatted version of the article will be published soon.

    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.

    Keywords: artificial intelligence, Health Policy, Regulatory Science, drug lifecycle, Drug approval process, Patient Safety

    Received: 23 May 2024; Accepted: 18 Jul 2024.

    Copyright: © 2024 OUALIKENE-GONIN, Jaulent, Thierry, Oliveira- Martins, BELGODERE, Maison and Ankri. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Wahiba OUALIKENE-GONIN, Agence Nationale de Sécurité du Médicament et Des Produits de Santé (ANSM), Paris, France

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.