The Adoption and Use of Artificial Intelligence and Machine Learning in Clinical Development.

Journal: Therapeutic innovation & regulatory science
Published Date: May 29, 2025

Abstract

BACKGROUND: The use of artificial intelligence (AI) and machine learning (ML) in drug discovery has been well documented, but measures of levels of adoption, investments, and efficiencies gained from its use in clinical development have not yet been developed, captured or published. AI/ML use in clinical development is expected to increase, but its impact has not yet been systematically measured until now.

Authors

  • Mary Jo Lamberti
    Tufts Center for the Study of Drug Development, Tufts University School of Medicine, Boston, MA, USA. Electronic address: mary_jo.lamberti@tufts.edu.
  • Maria I Florez
    Tufts Center for the Study of Drug Development, Tufts University School of Medicine, Boston, MA, USA.
  • Hana Do
    Tufts Center for the Study of Drug Development, Tufts University School of Medicine, Boston, MA, USA.
  • Stephanie Rosner
    Drug Information Association, Washington, DC, USA.
  • Timothé Ménard
    F. Hoffmann-La Roche, Basel, Switzerland. timothemenard@gmail.com.
  • Carrie Nielson
    Gilead Sciences, Inc., Foster City, CA, USA.
  • Amanda Donovan
    Takeda Pharmaceutical CO Ltd., Tokyo, Japan.
  • Jingjing Ye
    The Heart Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Regional Medical Center for Children, Hangzhou 310052, China.
  • Sathish Kaveripakam
    Novartis Pharma AG, Basel, CH-4056, Switzerland.
  • Birgit Schoeberl
    Novartis Pharma AG, Basel, CH-4056, Switzerland.
  • Alette R Hunt
    Novartis Pharma AG, Basel, CH-4056, Switzerland.
  • Helen Yeardley
    ICON Plc., Dublin, Ireland.

Keywords

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