Systems and methods for multivariate analysis of adverse event data

Abstract

The present disclosure describes systems and methods for multivarlate analysis of adverse event data. According to a first aspect, patient-specific genomic Information is used to optimize or de-risk therapy for the patient. According to other aspects of the invention, unknown drug targets are identified via adverse event data. According to still other espects, a medication is identified to exclude from use for an indication or from a clinical trial of another medication. According to another aspect, a predicted side effect profile is generated for a medication targeting a novel target. According to still another aspect, combination therapies are identified via adverse event data. According to another aspect, molecular interactions between a plurality of molecular entities are displayed in an intuitive format. According to still another aspect, molecular entities responsible for adverse event differences between similar indications are identified. According to still another aspect, genetic variants associated with adverse events in a clinical trial are identified.

Description

RELATED APPLICATIONS[0001]The present application claims priority to and the benefit of U.S. Provisional Patent Application No. 61 / 584,164, entitled “Translating Clinico-Molecular Data Into Safer, More Effective Drug Choices”, filed Jan. 6, 2012; U.S. Provisional Patent Application No. 61 / 605,625, entitled “Systems and Methods for Analysis of Adverse Event Data”, filed Mar. 1, 2012; U.S. patent application Ser. No. 13 / 446,917, entitled “Systems and Methods for Personalized De-Risking Based on Patient Genome Data”, filed Apr. 13, 2012; U.S. patent application Ser. No. 13 / 446,871, entitled “Systems and Methods for Identifying Unknown Drug Targets via Adverse Event Data”, filed Apr. 13, 2012; U.S. patent application Ser. No. 13 / 446,820, entitled “Systems and Methods for De-Risking Clinical Trials”, filed Apr. 13, 2012; and U.S. patent application Ser. No. 13 / 446,912, entitled “Systems and Methods for Using Adverse Event Data to Predict Potential Side Effects”, filed Apr. 13, 2012; each...

AI Technical Summary

Benefits of technology

[0086]In some embodiments of the system, the first biomolecular entity comprises a medication, drug class, target, or pathway. In other embodiments of the system, the second biomolecular entity comprises a medication, drug class, target, or pathway. In one embodiment, the analyzer is further configured for identifying a difference between a molecular interaction of the first biomolecular entity and a molecular interaction of the second biomolecular entity, and displaying the identified different molecular interaction of the second medication to the user. In another embodiment, the analyzer is further configured for identifying a reduced incidence of adverse events; and responsive to the identification, using the second biomolecular entity and first biomolecular entity as a combination therapy for a patient having the indication.

Problems solved by technology

However, analysis of such data is typically limited to simple univariate analysis, such as rates of adverse events associated with a medication.

Such analysis may fail to examine other factors and associations between medications or relationships between molecular entities associated with the medications, such as target (and off-target) proteins, enzymes, transporters, pathways, drug classes, or other information.

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