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Deep learning in pharmacogenomics: from gene regulation to patient stratification

    Alexandr A Kalinin

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    Statistics Online Computational Resource (SOCR), University of Michigan School of Nursing, Ann Arbor, MI 48109, USA

    Authors contributed equally

    Search for more papers by this author

    ,
    Gerald A Higgins

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    Authors contributed equally

    Search for more papers by this author

    ,
    Narathip Reamaroon

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    ,
    Sayedmohammadreza Soroushmehr

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    ,
    Ari Allyn-Feuer

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    ,
    Ivo D Dinov

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    Statistics Online Computational Resource (SOCR), University of Michigan School of Nursing, Ann Arbor, MI 48109, USA

    Michigan Institute for Data Science (MIDAS), University of Michigan, Ann Arbor, MI 48109, USA

    ,
    Kayvan Najarian

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    Department of Emergency Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    &
    Brian D Athey

    *Author for correspondence:

    E-mail Address: bleu@umich.edu

    Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    Michigan Institute for Data Science (MIDAS), University of Michigan, Ann Arbor, MI 48109, USA

    Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI 48109, USA

    Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI 48109, USA

    Published Online:https://doi.org/10.2217/pgs-2018-0008

    This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepigenomics; patient stratification from medical records; and the mechanistic prediction of drug response, targets and their interactions. Deep learning encapsulates a family of machine learning algorithms that has transformed many important subfields of artificial intelligence over the last decade, and has demonstrated breakthrough performance improvements on a wide range of tasks in biomedicine. We anticipate that in the future, deep learning will be widely used to predict personalized drug response and optimize medication selection and dosing, using knowledge extracted from large and complex molecular, epidemiological, clinical and demographic datasets.

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