Methods and systems for determination of an effective therapeutic regimen and drug discovery
AssigneeDNA-SEQ, Inc.
InventorsJanusz Sowadski, Davide Moiani
Life of this patent
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Abstract
The present invention relates to the discovery of a method for identifying a treatment regimen for a patient diagnosed with cancer, predicting patient resistance to therapeutic agents and identifying new therapeutic agents. Specifically, the present invention relates to the use of an algorithm to identify a mutation in a kinase, determine if the mutation is an activation or resistance mutation and then to suggest an appropriate therapeutic regimen. The invention also relates to the use of a pattern matching algorithm and a crystal structure library to predict the functionality of a gene mutation, predict the specificity of small molecule kinase inhibitors and for the identification of new therapeutic agents.
Claims16
A method of treating a subject with cancer comprising:
- a) obtaining a biologic sample from the subject;
- b) identifying at least one mutation in a gene sequence from the sample;
- c) executing with a computer at least one program embodied on a computer-readable medium, the at least one program including at least one pattern matching machine learning algorithm to determine if the at least one mutation is a cancer associated activation mutation or a therapeutic agent resistance mutation, and to search a crystal structure library to select at least one therapeutic agent to target the activation mutation or the resistance mutation, the pattern matching machine learning algorithm being trained on a collection of patterns of known cancer associated activation mutations, patterns of known therapeutic agent resistance mutations and patterns of known therapeutic agents, the pattern matching machine algorithm also classifying mutations based on a plurality of kinase DFG patterns;
- and
- d) treating the subject with the at least one therapeutic agent.
A method for identifying a therapeutic regimen or predicting resistance to a therapeutic regimen for a subject with cancer comprising:
- a) obtaining a biologic sample from the subject;
- b) identifying at least one mutation in a gene sequence from the sample;
- c) executing with a computer at least one program embodied on a computer-readable medium, the at least one program including at least one pattern matching machine learning algorithm to determine if the at least one mutation is a cancer associated activation mutation or a therapeutic agent resistance mutation, and to search a crystal structure library to select at least one therapeutic agent to target the activation mutation or the resistance mutation, the pattern matching machine learning algorithm being trained on a collection of patterns of known cancer associated activation mutations, patterns of known therapeutic agent resistance mutations and patterns of known therapeutic agents, the pattern matching machine algorithm also classifying mutations based on a plurality of kinase DFG patterns,
- thereby identifying a therapeutic regimen or predicting resistance to a therapeutic regimen.
Dependencies are inferred from the claim text.