The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 28, 2026

Filed:

Nov. 10, 2023
Applicants:

Genentech, Inc., South San Francisco, CA (US);

Hoffmann-la Roche Inc., Little Falls, NJ (US);

Ventana Medical Systems, Inc., Tucson, AZ (US);

Inventors:

Paolo Santiago Syjuco Ocampo, Los Altos Hills, CA (US);

Bernhard Stimpel, Basel, CH;

Yao Nie, Sunnyvale, CA (US);

Fahime Sheikhzadeh, Tucson, AZ (US);

Xiao Li, Foster City, CA (US);

Przemyslaw Szostak, Basel, CH;

Prasanna Porwal, Akola, IN;

Faranak Aghaei, Tucson, AZ (US);

Assignees:

Genentech, Inc., South San Francisco, CA (US);

Hoffmann-La Roche Inc., Little Falls, NJ (US);

Ventana Medical Systems, Inc., Tucson, AZ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 30/40 (2018.01); G06T 7/00 (2017.01); G16H 20/00 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G16H 30/40 (2018.01); G06T 7/0012 (2013.01); G16H 20/00 (2018.01); G16H 50/20 (2018.01);
Abstract

A method includes accessing a digital pathology image that depicts tumor cells sampled from a subject. A plurality of patches may be selected from the digital pathology image, wherein each of the patches depicts tumor cells. A mutation prediction may be generated for each of the patches, wherein the mutation prediction represents a prediction of a likelihood that an actionable mutation appears in the patch. Based on the plurality of mutation predictions, a prognostic prediction related to one or more treatment regimens for the subject may be generated. The prognostic prediction may be based on determining one or more mutational contexts of the digital pathology image as an unknown driver or a tumor suppressor, an oncogene driver mutation, or a gene fusion.


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