Systems and methods for assessing drug efficacy

Provided is a computer-implemented method, including inputting to a trained machine learning classifier genomic information of a non-training subject that includes features from a tumor sample, wherein the trained machine learning classifier trained on features of tumor samples obtained from trainin...

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Bibliographic Details
Main Authors Kang, Han, Wise, Aaron, Wang, Mengchi, Onuchic, Vitor Ferreira, Kruglyak, Kristina, Zhang, Shile
Format Patent
LanguageEnglish
Published 12.12.2019
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Summary:Provided is a computer-implemented method, including inputting to a trained machine learning classifier genomic information of a non-training subject that includes features from a tumor sample, wherein the trained machine learning classifier trained on features of tumor samples obtained from training subjects and their a responsiveness to checkpoint inhibition treatment and the machine-learning classifier is trained to predict responsiveness to the treatment, and generating a checkpoint inhibition responsiveness classification predictive of the subject's responding to the checkpoint inhibition with the trained machine-learning classifier, and reporting the checkpoint inhibition responsiveness classification using a graphical user interface. Also provided are a computer system for performing the method and a machine learning classifier trained by the method.
Bibliography:Application Number: AU20180375214