Systems and methods for personalized de-risking based on patient genome data

• US 9,779,214 B2
• Filed: 04/13/2012
• Issued: 10/03/2017
• Est. Priority Date: 01/06/2012
• Status: Active Grant

• Current Assignee: Molecular Health GmbH (Molecular Health AG)
• Original Assignee: Molecular Health GmbH (Molecular Health AG)
• Inventors: Jackson, David, Soldatos, Theodoros, Taglang, Guillaume, Zien, Alexander, Brock, Stephan
• Primary Examiner(s): Gort, Elaine
• Assistant Examiner(s): GO, JOHN P
• Application Number:
  US13/446,917
• Publication Number:
  US 20130179181A1
• Time in Patent Office: 1,999 Days
• Field of Search: 705 2, 705 3, 705 4
• 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 multi-variate analysis of genomic information of a patient and adverse event data of combination therapies, comprising:

receiving, by a multi-variate 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 and an identification of a second medication targeting a second protein to be prescribed to the patient;

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

retrieving, by the multi-variate analyzer by querying an adverse event database, a number of adverse event records each comprising an identification of co-medication of the first medication and the second medication, and an identification of an adverse event, wherein the first medication targets said first protein whose activity is altered by said genomic variant;

performing, by the multi-variate analyzer, a multi-variate analysis comprising;

determining, by the multi-variate analyzer based on the retrieved number of adverse event records, a likelihood of an adverse event occurring through co-medication of the first medication and the second medication, and

determining, by the multi-variate analyzer, that an adverse event corresponding to co-medication of the first medication and the second medication is likely to occur if the patient is prescribed the second medication and is not prescribed the first medication, responsive to the identified likelihood of an adverse event occurring through co-medication of the first medication and the second medication and the identification of the genomic variant of the patient; 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 determining a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises identifying, from the retrieved number of adverse event records, 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.

21. The method of claim 1, wherein identifying a first medication targeting the first protein further comprises searching the medication information database, by the analyzer, for entries identifying the first protein and retrieving a corresponding identification of a medication for each entry.

22. The method of claim 21, wherein retrieving the number of adverse event records further comprises, iteratively for each retrieved identified medication, searching the adverse event database for adverse events including said retrieved identified medication and the second medication.

23. The method of claim 1, further comprising identifying, by the analyzer, that the first medication is not prescribed and not to be prescribed to the patient;

and

wherein retrieving the number of adverse event records is performed responsive to identifying that the first medication is not prescribed and is not to be prescribed to the patient.

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 and an identification of a second medication targeting a second protein to be prescribed to the patient;

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

retrieving, by the analyzer by querying an adverse event database, a number of adverse event records each comprising an identification of co-medication of the first medication and the second medication, and an identification of an adverse event, wherein the first medication targets said first protein whose activity is altered by said genomic variant;

determining, by the analyzer based on the retrieved number of adverse event records, 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 and the identification of the genomic variant of the patient, that an adverse event corresponding to co-medication of the first medication and the second medication is not likely to occur if the patient is prescribed the second medication and is not prescribed the first 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 determining a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises identifying, from the retrieved number of adverse event records, 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 and an identification of a second medication targeting a second protein to be prescribed to the patient,

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

retrieving, by querying an adverse event database, a number of adverse event records each comprising an identification of co-medication of the first medication and the second medication, and an identification of an adverse event, wherein the first medication targets said first protein whose activity is altered by said genomic variant,

determining, based on the retrieved number of adverse event records, a likelihood of an adverse event occurring through co-medication of the first medication and the second medication, and

determining that an adverse event corresponding to co-medication of the first medication and the second medication is likely to occur if the patient is prescribed the second medication and is not prescribed the first medication, responsive to the identified likelihood of an adverse event occurring through co-medication of the first medication and the second medication and the identification of the genomic variant of the patient; 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 determining a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises identifying, from the retrieved number of adverse event records, 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 and an identification of a second medication targeting a second protein to be prescribed to the patient,

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

retrieving, by querying an adverse event database, a number of adverse event records each comprising an identification of co-medication of the first medication and the second medication, and an identification of an adverse event, wherein the first medication targets said first protein whose activity is altered by said genomic variant,

determining, based on the retrieved number of adverse event records, 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 corresponding to co-medication of the first medication and the second medication occurring through co-medication of the first medication and the second medication and the identification of the genomic variant of the patient, that an adverse event is not likely to occur if the patient is prescribed the second medication and is not prescribed the first 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 determining a likelihood of an adverse event occurring through co-medication of the first medication and the second medication comprises identifying, from the retrieved number of adverse event records, 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.