Genetic data analysis and database tools
View Patent ↗A computerized tool and method for delivery of pharmacogenetic and pharmacological information, comprising a core system having algorithms and databases for storing, collating, accessing, cross-referencing, and interpreting genetic and pharmacologic data, with a graphical user interface for a client network of providers of laboratory genetic testing services to access the core services under contract. The system includes “paypoints” in support of improved business models. Included are mechanisms for ‘pass through’ third party and insurance reimbursement for interpretive reports, insurance reimbursement for on-line access to pharmacogenetic information at the point of care, tools for market segmentation, and a conversion tool for capturing new subscribers. Also disclosed are tools and predictive algorithms for preventing drug-drug and drug-gene adverse drug reactions.
1. A method for predicting an adverse drug reaction or substance-factor interaction in a patient, which comprises:
a) for a list of patient factors selected from prescription drug usage, substance usage, personal characteristic, phenotype, genotype or clinical factors(s), performing a predictive calculation which comprises:
i) selecting culprits from the list, where a culprit is a factor having the property of being an inhibitor or an inducer, said culprits each having an intensity index INTX, where intensity index INTX indicates relative strength of inhibition or induction by each culprit;
ii) selecting a sublist of victims from the list, where a victim is a factor having the property of being a metabolic substrate of one or more metabolic routes Rn;
iii) identifying each metabolic route associated with said sublist of victims;
iv) identifying each interaction pair associated with said each metabolic route, each interaction pair consisting of a victim and a culprit having a known metabolic interaction;
v) for each victim of said each interaction pair: calculating a CP score using a processor, by multiplying the intensity index INTX associated with the culprit times a metabolic throughput proportion R.sub.1/1-n, where R.sub.1/1-n is calculated as the metabolic throughput of said each metabolic route Rn divided by a sum of the throughput of all metabolic pathways acting on the victim in parallel;
vi) summing the CP scores for each victim and for each interacting pair, and tabulating the sums .SIGMA.CP;
vii) from the sums .SIGMA.CP, calculating a predicted percent change AUC for each victim and for each interacting pair; and,
b) displaying a report tabulating patient identifier, patient phenotype, factors entered in said list, and percent change AUC for each victim, wherein an elevated percent change AUC is indicative of an adverse drug reaction or substrance:factor interaction.
2. The method of claim 1 , wherein said substance-factor interaction comprises a drug-gene interaction, a drug-drug interaction, or a combination thereof.
3. The method of claim 1 , wherein said list of patient factors comprises one or more drugs in a regimen, and said report is displayed to a physician prescribing said regimen or to a patient receiving said regimen.
4. The method of claim 1 , wherein said list of patient factors comprises one or more patient phenotypes or genotypes.
5. The method of claim 1 , wherein said calculation comprises:
a) for each said interaction pair, identifying any record(s) accessible in a first database of published reports of interactions between said victim and said culprit of said interaction pair;
b) if such said record(s) are identified, displaying in said report at least one note or warning abstracted from said record(s);
c) even if no such said record(s) are identified, but said predicted percent change AUC exceeds a threshold value; reporting a warning; and,
d) repeating steps a through c for each interaction pair, and reporting said notes or warnings for each said victim of each said interaction pair in said report.
6. The method of claim 5 , wherein said notes or warnings are ranked according to the potential severity of said adverse interaction.
7. The method of claim 1 , wherein said calculations comprise:
a) for any prescription drug or substance on said list of patient factors, identifying a class membership, wherein said class membership is defined by a side effect produced by all members of the class;
b) for any class membership identified therein, identifying any factors from the list having said class membership in common and forming a sublist thereof; and,
c) reporting said sublist of factors having said class membership in common, with a note advising that said side effect(s) can be additive.
8. The method of claim 1 , wherein said calculations comprise:
a) for any potential interaction pair for which said percent change AUC exceeds a threshold value, identifying a therapeutic class associated with said victim of said interaction pair;
b) identifying an alternate member of said therapeutic class and calculating an alternate percent change AUC for the alternate member; and,
c) reporting the alternate member and selecting a therapeutic alternative if the alternate percent change AUC does not exceed a threshold value.
9. The method of claim 1 , wherein said calculations comprise:
a) for any potential interaction pair for which said percent change AUC exceeds a threshold value, identifying a therapeutic class associated with said culprit of said interaction pair;
b) identifying an alternative member of said therapeutic class associated with an alternate metabolic route and calculating an alternate percent change AUC for the alternate member; and,
c) reporting the alternative member as a therapeutic alternative if the alternate percent change AUC does not exceed said threshold value. reaction associated with said change.
10. A method for providing pharmacogenetic guidance for preventing an adverse drug:drug or drug:substance reaction, which comprises:
a) for a list of patient factors selected from prescription drug usage, substance usage, personal characteristic, phenotype, genotype or clinical factors(s), performing a predictive calculation which comprises:
i) selecting culprits from the list, where a culprit is a factor having the property of being an inhibitor or an inducer, said culprits each having an intensity index INTX, where intensity index INTX indicates relative strength of inhibition or induction by each culprit;
ii) selecting a sublist of victims from the list, where a victim is a drug or substance having the property of being a metabolic substrate of one or more metabolic routes Rn;
iii) identifying each metabolic route associated with said sublist of victims;
iv) identifying each interaction pair associated with said each metabolic route, each interaction pair consisting of a victim and a culprit having a known metabolic interaction;
v) for each victim of said each interaction pair: calculating a CP score using a processor by multiplying the intensity index INTX associated with the culprit times a metabolic throughput proportion R.sub.1/1-n, where R.sub.1/1-n is calculated as the metabolic throughput of said each metabolic route Rn divided by a sum of the throughput of all metabolic pathways acting on the victim in parallel;
vi) summing the CP scores for each victim and for each interacting pair, and tabulating the sums .SIGMA.CP;
vii) from the sums .SIGMA.CP, calculating a predicted percent change AUC for each victim and for each interacting pair;
viii) from the sums .SIGMA.CP, calculating a predicted percent change AUC for each victim and for each interacting pair;
b) displaying a report tabulating patient identifier, patient phenotype, factors entered in said list, and percent change AUC for each victim; and,
c) updating said report when a change occurs in prescription drug usage or substance usage, said report including a prediction of a potential bioincompatibility if said percent change AUC exceeds a threshold value and pharmacogenetic guidance warning of a potential adverse reaction associated with said change.
11. The method of claim 10 , wherein said substance-factor interaction comprises a drug-gene interaction, a drug-drug interaction, or a combination thereof.
12. The method of claim 10 , wherein said list of patient factors comprises one or more drugs in a regimen, and said report is displayed to a physician prescribing said regimen or to a patient receiving said regimen.
13. The method of claim 10 , wherein said list of patient factors comprises one or more patient phenotypes or genotypes.
14. The method of claim 10 , wherein said calculation comprises:
a) for each said interaction pair, identifying any records(s) accessible in a first database of published reports of interactions between said victim and said culprit of said interaction pair;
b) if such said record(s) are identified, displaying in said report at least one note or warning abstracted from said record(s);
c) even if no such said record(s) are identified, but said predicted percent change AUC exceeds a threshold value; reporting a warning; and,
d) repeating steps a through c for each interaction pair, and reporting said notes or warnings for each said victim of each said interaction pair in said report.
15. The method of claim 14 , wherein said notes or warnings are ranked according to the potential severity of said adverse interaction.
16. The method of claim 10 , wherein said calculations comprise:
a) for any prescription drug or substance on said list of patient factors, identifying a class membership, wherein said class membership is defined by an adverse side effect produced by all members of the class;
b) for any class membership identified therein, identifying any factors from the list having said class membership in common and forming a sublist thereof; and,
c) reporting said sublist of factors having said class membership in common, with a note advising that said adverse side effect(s) can be additive.
17. The method of claim 10 , wherein said calculations comprise:
a) for any potential interaction pair for which said percent change AUC exceeds a threshold value, identifying a therapeutic class associated with said victim of said interaction pair;
b) identifying an alternative member of said therapeutic class associated with an alternate metabolic route and calculating an alternate percent change AUC for the alternate member; and,
c) reporting the alternative member as a therapeutic alternative if the alternate percent change AUC does not exceed said threshold value, thereby preventing a potential adverse drug:drug or drug:substance reaction.
18. The method of claim 10 , wherein said calculations comprise:
a) for any potential interaction pair for which said percent change AUC exceeds a threshold value, identifying a therapeutic class associated with said culprit of said interaction pair;
b) identifying an alternative member of said therapeutic class associated with an alternate metabolic route and calculating an alternate percent change AUC for the alternate member; and,
c) reporting the alternate member and selecting a therapeutic alternative if the alternate percent change AUC does not exceed a threshold value, thereby preventing a potential adverse drug:drug or drug:substance reaction.
19. The method of claim 1 , wherein said list of patient factors is enterable into a first graphical user interface in communication a first software engine and a report is displayed on said first graphical user interface or a network compatible device.
20. The method of claim 19 , comprising making a change to or an addition of a drug to said list of patient factors and displaying an updated report, thereby predicting any drug-factor interaction in the patient which may result from the change to or addition of said drug.
21. The method of claim 10 , wherein said list of patient factors is enterable into a first graphical user interface in communication a first software engine and a report is displayed on said first graphical user interface or a network compatible device.
22. The method of claim 21 , wherein said processor is digitally linked to a computerized network, said computerized network comprising a database having electronic medical records.