Paradigm drug response networks

A system for in silico analysis of data sets derived from omics data of cells, comprising:

• a pathway model database informationally coupled to a machine learning system and a pathway analysis engine;
• wherein the pathway model database is programmed to store 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;
• wherein the machine learning system is programmed to receive from the pathway model database the plurality of distinct data sets, and wherein the machine learning system is further programmed to identify 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;
• wherein the pathway analysis engine is programmed to receive at least one of the distinct data sets from the diseased cells and further programmed to modulate the determinant pathway element in the at least one distinct data set to produce a modified data set from the diseased cell;
• and
• wherein the machine learning system is programmed to identify a change in the status of the treatment parameter for the diseased cell using the modified data set.

A non-transient computer readable medium containing program instructions for causing a computer system in which a pathway model database is coupled to a machine learning system and a pathway analysis engine to perform a method comprising the steps of:

• transferring from the pathway model database to the machine learning system 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;
• 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.

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 cells treated with a candidate compound, 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 administration of the candidate compound to the cells;
• receiving, by the pathway analysis engine, at least one of the distinct data sets from the cells;
• associating, by the pathway analysis engine, the determinant pathway element in the at least one distinct data set with a specific pathway or druggable target, and producing an output that correlates the candidate compound with the specific pathway or druggable target.