Generative artificial intelligence empowers digital twins in drug discovery and clinical trials.

Journal: Expert opinion on drug discovery
Published Date:

Abstract

INTRODUCTION: The concept of Digital Twins (DTs) translated to drug development and clinical trials describes virtual representations of systems of various complexities, ranging from individual cells to entire humans, and enables in silico simulations and experiments. DTs increase the efficiency of drug discovery and development by digitalizing processes associated with high economic, ethical, or social burden. The impact is multifaceted: DT models sharpen disease understanding, support biomarker discovery and accelerate drug development, thus advancing precision medicine. One way to realize DTs is by generative artificial intelligence (AI), a cutting-edge technology that enables the creation of novel, realistic and complex data with desired properties.

Authors

  • Maria Bordukova
    Data & Analytics, Pharmaceutical Research and Early Development, Roche Innovation Center Munich (RICM), Penzberg, Germany.
  • Nikita Makarov
    Data & Analytics, Pharmaceutical Research and Early Development, Roche Innovation Center Munich (RICM), Penzberg, Germany.
  • Raul Rodriguez-Esteban
    Roche Pharmaceutical Research and Early Development, pRED Informatics, Roche Innovation Center, Basel, Switzerland.
  • Fabian Schmich
    From the Data Science, Pharmaceutical Research and Early Development Informatics (pREDi), Roche Innovation Center Munich (RICM), Penzberg, Germany.
  • Michael P Menden
    Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.