Han Chiao Kang

US Patent:

20200176083, Jun 4, 2020

Filed:

Dec 3, 2018

Appl. No.:

16/208149

Inventors:

- San Diego CA, US
Mengchi Wang - La Jolla CA, US
Aaron Wise - San Diego CA, US
Han Kang - San Diego CA, US
Vitor Ferreira Onuchic - San Diego CA, US
Kristina Kruglyak - San Diego CA, US

Assignee:

ILLUMINA, INC. - San Diego CA

International Classification:

G16B 40/20
C12Q 1/6886
G16H 50/20
G16H 50/50
G16B 45/00
G16B 50/30
G16B 50/20
G06F 17/15
G06F 17/16
G06F 17/18

Abstract:

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.