PARADIGM DRUG RESPONSE NETWORKS

摘要

Systems and methods are presented in which omics data from multiple cell or tissue samples are used to identify pathway elements that are associated with a treatment parameter of the cell or tissue (e.g., resistance towards a specific drug). So identified pathway elements are then modulated in silico in a statistical factor graph model to provide a modified data set that is re-evaluated with respect to the treatment parameter. Such systems and models are particularly useful for recommendation of multi-drug treatments for treatment-nave patients.

主权项

1. A method of in silico analysis of data sets derived from omics data of cells, comprising:
informationally coupling a pathway model database to a machine learning system and a pathway analysis engine; wherein the pathway model database stores a plurality of distinct data sets derived from omics data of a plurality of distinct diseased cells, respectively, and wherein each data set comprises a plurality of pathway element data; receiving, by the machine learning system, the plurality of distinct data sets; identifying, by the machine learning system, a determinant pathway element in the plurality of distinct data sets that is associated with a status of a treatment parameter of the diseased cells; receiving, by the pathway analysis engine, at least one of the distinct data sets from the diseased cells; modulating, by the pathway analysis engine, the determinant pathway element in the at least one distinct data set to produce a modified data set from the diseased cell; and identifying, by the machine learning system and using the modified data set, a change in the status of the treatment parameter for the diseased cell.