Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis.

Journal: Journal of medicinal chemistry
Published Date: Aug 27, 2020

Abstract

Artificial intelligence and machine learning have demonstrated their potential role in predictive chemistry and synthetic planning of small molecules; there are at least a few reports of companies employing synthetic planning into their overall approach to accessing target molecules. A data-driven synthesis planning program is one component being developed and evaluated by the Machine Learning for Pharmaceutical Discovery and Synthesis (MLPDS) consortium, comprising MIT and 13 chemical and pharmaceutical company members. Together, we wrote this perspective to share how we think predictive models can be integrated into medicinal chemistry synthesis workflows, how they are currently used within MLPDS member companies, and the outlook for this field.

Authors

  • Thomas J Struble
    Department of Chemical Engineering, Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA whgreen@mit.edu kfjensen@mit.edu.
  • Juan C Alvarez
    Computational and Structural Chemistry, Merck & Co. Inc., Kenilworth, New Jersey 07033, United States.
  • Scott P Brown
    Sunovion Pharmaceuticals Inc., Marlborough, Massachusetts 01752, United States.
  • Milan Chytil
    Sunovion Pharmaceuticals Inc., Marlborough, Massachusetts 01752, United States.
  • Justin Cisar
    Janssen Research & Development LLC, Spring House, Pennsylvania 19477, United States.
  • Renee L DesJarlais
    Janssen Research & Development LLC, Spring House, Pennsylvania 19477, United States.
  • Ola Engkvist
    Hit Discovery, Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, AstraZeneca R&D Gothenburg, 431 83, Mölndal, Sweden.
  • Scott A Frank
    Eli Lilly and Company, Indianapolis, Indiana 46285, United States.
  • Daniel R Greve
    LEO Pharma A/S, Industriparken 55, DK-2750 Ballerup, Denmark.
  • Daniel J Griffin
    Amgen Inc., Cambridge, Massachusetts 02141, United States.
  • Xinjun Hou
    Pfizer Inc., Cambridge, Massachusetts 02139, United States.
  • Jeffrey W Johannes
    Medicinal Chemistry, Early Oncology, Oncology R&D, AstraZeneca, Boston, Massachusetts 02451, United States.
  • Constantine Kreatsoulas
    GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States.
  • Brian Lahue
    Computational and Structural Chemistry, Merck & Co. Inc., Kenilworth, New Jersey 07033, United States.
  • Miriam Mathea
    BASF SE , Ludwigshafen 67063 , Germany.
  • Georg Mogk
    Bayer GmbH, D-51368 Leverkusen, Germany.
  • Christos A Nicolaou
  • Andrew D Palmer
    BASF SE, Carl-Bosch-Strasse 38, 67056 Ludwigshafen am Rhein, Germany.
  • Daniel J Price
    GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States.
  • Richard I Robinson
    Novartis Institutes for BioMedical Research, Cambridge, Massachusetts 02139, United States.
  • Sebastian Salentin
    BASF SE, Carl-Bosch-Strasse 38, 67056 Ludwigshafen am Rhein, Germany.
  • Li Xing
    WuXi AppTec Co., Ltd, Shanghai, China.
  • Tommi Jaakkola
    Computer Science and Artificial Intelligence Laboratory , MIT , Cambridge , Massachusetts 02139 , United States.
  • William H Green
    Department of Chemical Engineering, Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA whgreen@mit.edu kfjensen@mit.edu.
  • Regina Barzilay
    Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology , 77 Massachusetts Avenue , Cambridge , MA 02139 , USA . Email: regina@csail.mit.edu.
  • Connor W Coley
    Department of Chemical Engineering, Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA whgreen@mit.edu kfjensen@mit.edu.
  • Klavs F Jensen
    Department of Chemical Engineering, Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge MA 02139 USA whgreen@mit.edu kfjensen@mit.edu.

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