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

ABSTRACT: Anti-PD-1 immunotherapy has recently shown tremendous success for the treatment of several aggressive cancers. However, variability and unpredictability in treatment outcome have been observed, and are thought to be driven by patient-specific biology and interactions of the patient's immune system with the tumor. Here we develop an integrative systems biology and machine learning approach, built around clinical data, to predict patient response to anti-PD-1 immunotherapy and to improve the response rate. Using this approach, we determine biomarkers of patient response and identify potential mechanisms of drug resistance. We develop systems biology informed neural networks (SBINN) to calculate patient-specific kinetic parameter values and to predict clinical outcome. We show how transfer le

SUBMITTER: Przedborski M 

PROVIDER: S-EPMC8282606 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature