Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade

Michelle Przedborski; Munisha Smalley; Saravanan Thiyagarajan; Aaron Goldman; Mohammad Kohandel

doi:10.1038/s42003-021-02393-7

Communications Biology (Jul 2021)

Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade

Michelle Przedborski,
Munisha Smalley,
Saravanan Thiyagarajan,
Aaron Goldman,
Mohammad Kohandel

Affiliations

Michelle Przedborski: Department of Applied Mathematics, University of Waterloo
Munisha Smalley: Integrative Immuno Oncology Center, Mitra Biotech
Saravanan Thiyagarajan: Integrative Immuno Oncology Center, Mitra Biotech
Aaron Goldman: Division of Engineering in Medicine, Brigham and Women’s Hospital
Mohammad Kohandel: Department of Applied Mathematics, University of Waterloo

DOI: https://doi.org/10.1038/s42003-021-02393-7
Journal volume & issue: Vol. 4, no. 1
pp. 1 – 15

Abstract

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Michelle Przedborski et al. report an integrative systems biology and machine learning method for predicting cancer patient responses to immunotherapy treatment. Using their method, they identify several new drug combinations that could potentially improve treatment protocols for immunotherapy.

Published in Communications Biology

ISSN: 2399-3642 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General)
Website: https://www.nature.com/commsbio/

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