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:
May. 18, 2021

Filed:

Jun. 30, 2014
Applicant:

Nantomics, Llc, Culver City, CA (US);

Inventors:

Stephen Charles Benz, Santa Cruz, CA (US);

Shahrooz Rabizadeh, Los Angeles, CA (US);

Christopher Szeto, Soquel, CA (US);

Paul Weingarten, Anaheim, CA (US);

Chunlin Tao, Newport Coast, CA (US);

Assignee:

NantOmics, LLC, Culver City, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); C07D 403/14 (2006.01); C07D 403/12 (2006.01); A61P 35/00 (2006.01); A61K 31/506 (2006.01); C07D 401/14 (2006.01); C07D 417/14 (2006.01); C07D 413/14 (2006.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); A61K 31/506 (2013.01); A61P 35/00 (2018.01); C07D 401/14 (2013.01); C07D 403/12 (2013.01); C07D 403/14 (2013.01); C07D 413/14 (2013.01); C07D 417/14 (2013.01);
Abstract

The present inventive subject matter provides apparatus, systems, and methods in which a diagnostic test is identified, where the diagnostic test is for determining whether a particular treatment is effective for a particular patient based on one or more characteristics of a patient's cells. When a treatment is developed with the potential to treat one or more diseases, the drug can have different effects on different cell lines related to the diseases. A machine learning system is programmed to infer a measurable cell characteristic, out of many different measurable cell characteristics, that has a desirable correlation with the sensitivity data of different cell lines to a treatment. The machine learning system is programmed to then determine, based on the correlation, a threshold level of the cell characteristic the patient should exhibit in order to recommend administering the treatment.


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