Systems and methods for quantification and presentation of medical risk arising from unknown factors

• US 10,210,312 B2
• Filed: 01/31/2014
• Issued: 02/19/2019
• Est. Priority Date: 02/03/2013
• Status: Active Grant

• Current Assignee: Youscript Technologies LLC
• Original Assignee: YouScript Inc. (Invitae Corporation)
• Inventors: Coleman, Howard C., Patterson, Robert D., Oesterheld, Jessica, Pany, Rajeev V., Ashcraft, Kristine
• Primary Examiner(s): Shah, Kamini S
• Assistant Examiner(s): Khan, Iftekhar A
• Application Number:
  US14/170,367
• Publication Number:
  US 20140222400A1
• Time in Patent Office: 1,845 Days
• Field of Search: 703 2
• CPC Class Codes: G16C 20/30 Prediction of properties of chemical compounds, compositions or mixtures
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage

Abstract

Example methods of quantifying known and unknown risks of an adverse drug event in an individual based on various factors are disclosed. In some embodiments, factors include known drug-drug interactions and unknown phenotypes of cytochromes. Quantification may be based on severity of the adverse drug event/and or probability of occurrence in some embodiments. Example methods of displaying the quantified risk are also disclosed. In one embodiment, the risk of individuals is aggregated to display the risk of a population.

Claims

1. A method comprising:

receiving, at a computing system, identification of at least one drug;

selecting, using the computing system, certain factors affecting exposure of an individual to the at least one drug, wherein at least one of the factors comprises a genotype, wherein at least one of the certain factors are known factors for the individual and at least one of the certain factors are unknown factors for the individual;

quantifying, using the computing system, a first expected effect on metabolism of the drug by the individual due to the known factors by identifying metabolic routes used by the at least one drug and summing an expected effect on metabolism of the drug using each of the metabolic routes due to each of the known factors;

compiling a matrix of expected effects by evaluating a plurality of interactions between the at least one drug, the genotype, each of the known factors, and each of the unknown factors;

removing, from the matrix of expected effects, certain interactions from the plurality of interactions that are mild or result in no clinical effect, wherein the certain interactions are identified in part by comparing each of the plurality of interactions against a matrix of known adverse interactions and reaction severities stored in a memory;

quantifying, using the computing system, a second expected effect on metabolism of the drug by the individual due to the known factors and the unknown factors, wherein quantifying the second expected effect comprises utilizing the matrix of expected effects and identifying multiple possible values of one of the unknown factors and summing an expected effect on metabolism of the drug using each of the multiple possible values, wherein quantifying the second expected effect further comprises weighting the expected effect on metabolism of the drug using each of the multiple possible values in accordance with a probability of each of the multiple possible values being an actual value of the factor for the individual, wherein the certain factors include a phenotype and wherein weighting the expected effect on metabolism of the drug using each of the multiple possible values in accordance with a probability of each of the multiple possible values being an actual value of the factor for the individual comprises using a matrix of probabilities of occurrence of phenotypes;

generating, using the computing system, a numerical representation of risk based at least in part on the first expected effect and the second expected effect; and

displaying, using the computing system, the numerical representation of risk in an interaction report, wherein the interaction report is tailored to one or more clinical practices.

2. The method of claim 1, wherein the certain factors include a phenotype.

3. The method of claim 1, further comprising providing the first and second expected effect to a user.

4. The method of claim 3, wherein the first and second expected effects are provided graphically on an electronic display.

5. The method of claim 1, wherein the at least one drug is provided by a user.

6. The method of claim 1, wherein the probabilities are based on human population data.

7. The method of claim 6, further comprising modifying the probabilities based, at least in part, on additional data provided by a user, wherein the additional data comprises at least one of gender, race, or ethnicity.

8. A non-transitory computer readable medium encoded with executable instructions comprising instructions for:

identifying metabolic routes used in metabolizing at least one drug;

selecting certain factors affecting exposure of an individual to the at least one drug, wherein at least one of the factors comprises a phenotype, wherein at least one of the certain factors are known factors for the individual and at least one of the certain factors are unknown factors for the individual;

quantifying a first expected effect on metabolism of the drug by the individual due to the known factors by summing an expected effect on metabolism of the drug using each of the metabolic routes due to each of the known factors;

compiling a matrix of expected effects by evaluating a plurality of interactions between the at least one drug, the phenotype, each of the known factors, and each of the unknown factors;

removing, from the matrix of expected effects, certain interactions from the plurality of interactions that are mild or result in no clinical effect, wherein the certain interactions are identified in part by comparing each of the plurality of interactions against a matrix of known adverse interactions and reaction severities stored in a memory;

quantifying a second expected effect on metabolism of the drug by the individual due to the known factors and the unknown factors, wherein quantifying the second expected effect comprises utilizing the matrix of expected effects and identifying multiple possible values of one of the unknown factors and summing an expected effect on metabolism of the drug using each of the multiple possible values, wherein quantifying the second expected effect further comprises weighting the expected effect on metabolism of the drug using each of the multiple possible values in accordance with a probability of each of the multiple possible values being an actual value of the factor for the individual, wherein the certain factors include the phenotype and wherein weighting the expected effect on metabolism of the drug using each of the multiple possible values in accordance with a probability of each of the multiple possible values being an actual value of the factor for the individual comprises using a matrix of probabilities of occurrence of phenotypes;

generating a numerical representation of risk based at least in part on the first expected effect and the second expected effect; and

displaying the numerical representation of risk in an interaction report, wherein the interaction report is tailored to one or more clinical practices.