SYSTEMS AND METHODS FOR PERSONALIZED DE-RISKING BASED ON PATIENT GENOME DATA

• US 20130179181A1
• Filed: 04/13/2012
• Published: 07/11/2013
• Est. Priority Date: 01/06/2012
• Status: Active Grant

• Current Assignee: Molecular Health GmbH (Molecular Health AG)
• Original Assignee: Molecular Health
• Inventors: Jackson, David, Soldatos, Theodoros, Taglang, Guillaume, Zien, Alexander, Brock, Stephan
• Granted Patent: US 9,779,214 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage

Abstract

The present disclosure describes systems and methods for using patient-specific genomic information to optimize or de-risk therapy for the patient. A user may identify a medication for consideration for prescription to a patient, and a genetic variant of the patient affecting a first protein. An analyzer may identify a second medication targeting the first protein, and may retrieve adverse event data from an adverse event database for patients co-medicated with both the first medication and second medication. The analyzer may determine, based on rates of adverse events, the likelihood of an adverse event occurring through co-medication of the first medication and second medication. Based on the likelihood, and based on a correspondence or non-correspondence between a protein activation characteristic of the first medication and the effect of the genetic variant of the patient, the analyzer may indicate or contra-indicate the first medication for the patient.

Claims

1. A method for personalized de-risking of medications based on genomic information of a patient and adverse event data of combination therapies, comprising:

receiving, by an analyzer executed by a processor of computing device from a user, an identification of a genomic variant of a patient altering activity of a first protein;

identifying, by the analyzer from a medication information database, responsive to receiving the identification of the genomic variant, a first medication targeting the first protein;

receiving, by the analyzer from the user, an identification of a second medication targeting a second protein to be prescribed to the patient;

identifying, by the analyzer from an adverse event database, a likelihood of an adverse event occurring through co-medication of the first medication and the second medication;

determining, by the analyzer, that an adverse event is likely to occur if the patient is prescribed the second medication, responsive to the identified likelihood of an adverse event occurring through co-medication of the first medication and the second medication; and

displaying, by a display module executed by computing device, the second medication as contraindicated responsive to the determination.

2. The method of claim 1, wherein the genomic variant is activating, and wherein the first medication is an agonist of the first protein.

3. The method of claim 1, wherein the genomic variant is inactivating, and wherein the first medication is an antagonist of the first protein.

4. The method of claim 1, wherein identifying a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises querying the adverse event database for a rate of adverse event records including identification of co-medication of the first medication and the second medication;

and identifying the rate as being above a predetermined threshold.

5. The method of claim 1, wherein determining that an adverse event is likely to occur if the patient is prescribed the second medication comprises identifying an activation characteristic of the genomic variant, and identifying a corresponding activation characteristic of the first medication.

6. A method for personalized de-risking of medications based on genomic information of a patient and adverse event data of combination therapies, comprising:

receiving, by an analyzer executed by a processor of a computing device from a user, an identification of a genomic variant of a patient altering activity of a first protein;

identifying, by the analyzer from a medication information database, responsive to receiving the identification of the genomic variant, a first medication targeting the first protein;

receiving, by the analyzer from the user, an identification of a second medication targeting a second protein to be prescribed to the patient;

identifying, by the analyzer from an adverse event database, a likelihood of an adverse event occurring through co-medication of the first medication and the second medication;

determining, by the analyzer responsive to the identified likelihood of an adverse event occurring through co-medication of the first medication and the second medication, that an adverse event is not likely to occur if the patient is prescribed the second medication; and

displaying, by a display module executed by the computing device, the second medication as indicated, responsive to the determination.

7. The method of claim 6, wherein the genomic variant is inactivating, and wherein the first medication is an agonist of the first protein.

8. The method of claim 6, wherein the genomic variant is activating, and wherein the first medication is an antagonist of the first protein.

9. The method of claim 6, wherein identifying a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises querying the adverse event database for a rate of adverse event records including identification of co-medication of the first medication and the second medication;

and identifying the rate as being below a predetermined threshold.

10. The method of claim 6, wherein determining that an adverse event is not likely to occur if the patient is prescribed the second medication comprises identifying an activation characteristic of the genomic variant, and identifying a non-corresponding activation characteristic of the first medication.

11. A system for personalized de-risking of medications based on genomic information of a patient and adverse event data of combination therapies, comprising:

a computing device comprising a processor executing

an analyzer, configured for

receiving, from a user, an identification of a genomic variant of a patient altering activity of a first protein,

identifying, from a medication information database, responsive to receiving the identification of the genomic variant, a first medication targeting the first protein,

receiving, from the user, an identification of a second medication targeting a second protein to be prescribed to the patient,

identifying, from an adverse event database, a likelihood of an adverse event occurring through co-medication of the first medication and the second medication, and

determining that an adverse event is likely to occur if the patient is prescribed the second medication, responsive to the identified likelihood of an adverse event occurring through co-medication of the first medication and the second medication; and

a display module, configured for displaying to the user the second medication as contraindicated responsive to the determination.

12. The system of claim 11, wherein the genomic variant is activating, and wherein the first medication is an agonist of the first protein.

13. The system of claim 11, wherein the genomic variant is inactivating, and wherein the first medication is an antagonist of the first protein.

14. The system of claim 11, wherein identifying a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises querying the adverse event database for a rate of adverse event records including identification of co-medication of the first medication and the second medication;

and identifying the rate as being above a predetermined threshold.

15. The system of claim 11, wherein determining that an adverse event is likely to occur if the patient is prescribed the second medication comprises identifying an activation characteristic of the genomic variant, and identifying a corresponding activation characteristic of the first medication.

16. A system for personalized de-risking of medications based on genomic information of a patient and adverse event data of combination therapies, comprising:

a computing device comprising a processor executing

an analyzer, configured for

receiving from a user, an identification of a genomic variant of a patient altering activity of a first protein,

identifying, from a medication information database, responsive to receiving the identification of the genomic variant, a first medication targeting the first protein,

receiving, from the user, an identification of a second medication targeting a second protein to be prescribed to the patient,

identifying, from an adverse event database, a likelihood of an adverse event occurring through co-medication of the first medication and the second medication, and

determining, responsive to the identified likelihood of an adverse event occurring through co-medication of the first medication and the second medication, that an adverse event is not likely to occur if the patient is prescribed the second medication; and

a display module configured for displaying, to the user, the second medication as indicated, responsive to the determination.

17. The system of claim 16, wherein the genomic variant is inactivating, and wherein the first medication is an agonist of the first protein.

18. The system of claim 16, wherein the genomic variant is activating, and wherein the first medication is an antagonist of the first protein.

19. The system of claim 16, wherein identifying a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises querying the adverse event database for a rate of adverse event records including identification of co-medication of the first medication and the second medication;

and identifying the rate as being below a predetermined threshold.

20. The system of claim 16, wherein determining that an adverse event is not likely to occur if the patient is prescribed the second medication comprises identifying an activation characteristic of the genomic variant, and identifying a non-corresponding activation characteristic of the first medication.