Machine Learning in Drug Discovery and Development Part 1: A Primer.

Journal: CPT: pharmacometrics & systems pharmacology
Published Date: Mar 1, 2020

Abstract

Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.

Authors

  • Alan Talevi
    Laboratory of Bioactive Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences, University of La Plata (UNLP) - 47 & 115, La Plata (1900), Buenos Aires, Argentina.
  • Juan Francisco Morales
    Laboratorio de Investigación y Desarrollo de Bioactivos (LIDeB), Faculty of Exact Sciences, National University of La Plata (UNLP), Buenos Aires, Argentina.
  • Gregory Hather
    Statistical & Quantitative Sciences, Takeda Pharmaceuticals, Cambridge, Massachusetts, USA.
  • Jagdeep T Podichetty
    Quantitative Medicine, Critical Path Institute, Tucson, Arizona, USA.
  • Sarah Kim
    Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA.
  • Peter C Bloomingdale
    Quantitative Pharmacology and Pharmacometrics, Merck & Co. Inc, Kenilworth, New Jersey, USA.
  • Samuel Kim
    Canary Speech LLC, Provo, Utah, USA.
  • Jackson Burton
    Quantitative Medicine, Critical Path Institute, Tucson, Arizona, USA.
  • Joshua D Brown
    Howard Hughes Medical Institute, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA.
  • Almut G Winterstein
    Center for Drug Evaluation and Safety, Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, Florida, USA.
  • Stephan Schmidt
    Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA.
  • Jensen Kael White
    Quantitative Medicine, Critical Path Institute, Tucson, Arizona, USA.
  • Daniela J Conrado
    e-Quantify LLC, La Jolla, California, USA.

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