Models and Machines: How Deep Learning Will Take Clinical Pharmacology to the Next Level.

Journal: CPT: pharmacometrics & systems pharmacology
Published Date:

Abstract

Recent advances in machine learning (ML) have led to enthusiasm about its use throughout the biopharmaceutical industry. The ML methods can be applied to a wide range of problems and have the potential to revolutionize aspects of drug development. The incorporation of ML in modeling and simulation (M&S) has been eagerly anticipated, and in this perspective, we highlight examples in which ML and M&S approaches can be integrated as complementary parts of a clinical pharmacology workflow.

Authors

  • Lucy Hutchinson
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
  • Bernhard Steiert
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
  • Antoine Soubret
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
  • Jonathan Wagg
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
  • Alex Phipps
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Welwyn, Welwyn, UK.
  • Richard Peck
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
  • Jean-Eric Charoin
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
  • Benjamin Ribba
    Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.