Method and system for the analysis and association of patient-specific and population-based genomic data with drug safety adverse event data

A system for assessing and analyzing one or more drugs, adverse effects and associated risks, and patient information resulting from the use of at least one drug of interest, comprising:

• a relational database comprising source data, wherein the source data comprises adverse event data, drug information and patient information, wherein data form sources not already in a relational database structure are parsed into a relational database structure;
• an assemblage of cases comprising patient information, drug information and adverse effects, wherein each said case contains patient information, information related to a drug administered to that patient, and a description of an adverse drug reaction;
• a selector for selecting one or more cases for analysis;
• a profiler using statistical analysis conducted by said relational database across a set of cases to determine whether there is an indication of an association among a drug, a reaction or group of reactions and a genotype and the distribution of that association in a population, wherein profiles created by said profiler comprise the results of said statistical analysis that describes the behavior of the drug of interest based on patient genotype from multiple cases related to the safety of the at least one drug, wherein one or more filters may be used to select among available variables to permit a recalculation of the statistical analysis;
• at least one data mining engine for submitting the results of the statistical analysis in order to compare said results against selected criteria to extract data of interest;
• and
• an output device for displaying the output from the data mining engine;
• wherein the analysis of the data collected involves parsing a population segment data into a plurality of population segments;
• wherein the analysis of the data collected involves parsing a drug safety data based on a genetic perspective;
• wherein the drug of interest is analyzed using a plurality of metabolic pathways;
• wherein a first metabolic pathway includes the parsed population segment data relating to population segments having differing rates of metabolism;
• wherein a second metabolic pathway includes the parsed drug safety data relating to drug safety data based on a genetic perspective;
• wherein the first and the second metabolic pathways are assimilated;
• and
• wherein the first and the second metabolic pathways are correlated.

A method for assessing and analyzing one or more drugs, adverse effects and associated risks, and patient information resulting from the use of at least one drug of interest, comprising:

• collecting data from a plurality of sources comprising drug information, adverse effects relating to drugs and patient information;
• cleaning the collected data;
• placing the collected data into a data structure, wherein data from sources not already in a relational database structure are parsed into a relational database structure;
• generating a relational database for relating drug information, adverse effects and patient information;
• assembling said patient information, drug information and adverse effects into individual cases, wherein each said case contains patient information, information related to a drug administered to that patient and a description of an adverse drug reaction;
• identifying a patient genotype and at least one drug proposed to be administered to a patient having said genotype;
• using said relational database to conduct statistical analysis across a set of cases to determine whether there is an indication of association among a drug, a reaction or group of reactions and a genotype and the distribution of that association in a population;
• creating a profile comprising the results of said statistical analysis that describes the behavior of the drug of interest based on patient genotype from multiple cases related to the safety of the at least one drug, wherein one or more filters is employed to select among available variables to permit recalculation of the statistical analysis;
• submitting the results of the statistical analysis to at least one data mining engine to compare said results against selected criteria to extract data of interest;
• and
• displaying the output from the data mining engine through an output device;
• wherein the cleaning of the collected data includes identifying a synonymous term, a misspelling of a term, or a variation of a term for the drug or a term for the adverse effect;
• wherein the cleaning of the collected data further includes labeling the identified term as a verbatim term;
• wherein the analysis of the collected data involves parsing a population segment data into a plurality of population segments, the population segments having differing rates of metabolism;
• wherein the analysis of the data collected involves parsing a drug safety data based on a genetic perspective;
• wherein the drug of interest is analyzed using two or more metabolic pathways;
• wherein a first metabolic pathway includes the parsed population segment data relating to population segments having differing rates of metabolism;
• wherein a second metabolic pathway includes the parsed drug safety data relating to drug safety data based on a genomic perspective;
• wherein the first and the second metabolic pathways are assimilated;
• and
• wherein the first and the second metabolic pathways are correlated.