Genetic Data Analysis and Database Tools
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 - 11 . (canceled)
12 . A method for preventing an adverse drug event, which comprises:
a) entering a patient identifier on a graphical user interface;
b) entering, retrieving or modifying a patient treatment regimen, wherein said patient treatment regimen comprises a list of any drugs, substances, genotypes, phenotypes, or clinical factors to be associated with said patient identifier;
c) identifying a victim-culprit interaction that defines a first interaction pair on said list, wherein said first interaction pair comprises a first victim and a first culprit which interact by at least one metabolic or transport pathway to produce a change in activity of said victim, and predicting a level of severity of the victim-culprit interaction according to an algorithm for calculating a change in patient exposure to said first victim; and,
d) graphically displaying a warning of the victim-culprit interaction and level of severity thereof, if any, on said graphical user interface so that said patient treatment regimen may be modified if needed to prevent an adverse drug event.
13 . The method of claim 12 , wherein said adverse drug event is associated with a drug:drug interaction and said culprit is a drug from said list.
14 . The method of claim 12 , wherein said adverse drug event is associated with a drug:substance interaction and said culprit is a substance from said list.
15 . The method of claim 12 , wherein said adverse drug event is associated with a drug:genotype or drug:phenotype interaction and said culprit is a genotype or a phenotype, and wherein said genotype or phenotype is determined from genetic testing and is associated with said patient identifier.
16 . The method of claim 12 , wherein said adverse drug event is associated with a substance:factor interaction and said culprit is a clinical factor from said list.
17 . The method of claim 12 , wherein said change in patient exposure is calculated by multiplying an intensity factor (INTX) associated with the intensity of the interaction between said first culprit and said first victim times a fraction (R 1/1-n ) indicative of the fraction of the metabolism or transport modulated by said first culprit.
18 . The method of claim 12 , which further comprises predicting from said list a plurality of victim-culprit interactions that define a plurality of interaction pairs, wherein each said interaction pair comprises a victim and a culprit which interact by at least one metabolic or transport pathway to produce a change in patient exposure to the victim, wherein said prediction is made by an algorithm for calculating a change in patient exposure to an individual victim by summing the changes for all interaction pairs involving said individual victim, and further comprising graphically displaying a warning or warnings for the predicted victim-culprit interaction or interactions and level of severity thereof on said graphical user interface so that said patient treatment regimen may be modified if needed to prevent an adverse drug event.
19 . The method of claim 18 , wherein the change in patient exposure for any one victim having a plurality of interaction pairs associated with a plurality of culprits acting thereon is obtained by multiplying an intensity factor (INTX) associated with the intensity of the interaction between said any one victim and each culprit times a fraction (R 1/1-n ) of the metabolism or transport of the any one victim modulated by each culprit, and then summing the changes for said plurality of interaction pairs.
20 . The method of claim 18 , wherein said plurality of victim-culprit interactions include drug:drug interaction, drug:substance interaction, drug:gene interaction, drug:phenotype interaction, substance:factor interaction, or a combination thereof
21 . The method of claim 18 , wherein said plurality of victim-culprit interactions include culprits selected from food substance, herbal substance, over the counter medication, recreational drug use, alcohol use, history of smoking, obesity, prescription drug use, genetic polymorphism, genetic sequence, phenotype, pregnancy, gender and age, or a combination thereof.
22 . The method of claim 18 , wherein said plurality of victim-culprit interactions are selected from inhibition, inhibition of metabolism, inhibition of transport, induction, induction of metabolism, induction of transport, or a combination thereof.
23 . The method of claim 19 , wherein said plurality of victim-culprit interactions include culprits involving a Cytochrome P450-mediated reaction, a Phase I reaction, a Phase II reaction, an oxidation, a reduction, a hydrolysis reaction, a cyclization reaction, a decyclization reaction, a conjugation reaction, a transporter uptake, an organ specific transporter uptake, a transporter efflux, an elimination reaction, or a combination thereof.
24 . The method of claim 23 , wherein the fraction (R 1/1-n ) of metabolism or transport by each of a plurality of metabolic or transport pathways acting on each victim is the fraction of metabolic or transport throughput occurring by each of said plurality of metabolic pathways divided by the total metabolic or transport throughput occurring by all parallel pathways (R 1-n ).
25 . The method claim 12 , wherein said method is implemented on a computerized network, said network comprising a computer or server having a first software engine in digital communication with said graphical user interface, at least one database, and computer-executable instructions for implementing said predictive algorithm when performing operations on said list.
26 . The method of claim 18 , wherein said method is implemented on a computerized network, said network comprising a computer or server having a first software engine in digital communication with said graphical user interface, at least one database, and computer-executable instructions for implementing said predictive algorithm when performing operations on said list.
27 . The method of claim 12 , further comprising
a) for any interaction pair for which said change in exposure for said first victim exceeds a threshold level associated with a potential adverse drug event, identifying a therapeutic class associated with said first victim and a therapeutic class associated with said first culprit;
b) identifying at least one alternative member for each said therapeutic class and calculating a change in patient exposure thereto; and,
c) if said alternative member does not cause a change in patient exposure exceeding a threshold level associated with a potential adverse drug event, displaying the alternative member, whereby said alternative member may be substituted in said proposed patient treatment regimen by a prescriber so that an adverse drug event is prevented.
28 . The method of claim 27 , comprising identifying said at least one alternative member of said therapeutic class from a reimbursement eligibility list or formulary list associated with said patient identifier.
29 . The method of claim 18 , further comprising
a) for any drug or substance on said list, identifying a class membership, wherein said class membership is defined by a side effect associated with the class;
b) for any class membership identified therein, identifying any plurality of drugs or substances from the list sharing said class membership in common and forming a sublist thereof; and,
c) displaying said sublist of factors sharing said class membership in common, with a note advising that said side effect can be additive.
30 . The method of claim 12 , further comprising
a) for any first drug member on said list which is a member of a therapeutic class but does not meet reimbursement eligibility requirements, identifying a substitute member of said therapeutic class having reimbursement eligibility;
b) if the substitute member having reimbursement eligibility does not cause a change in patient exposure exceeding a threshold level associated with a potential adverse drug event, then displaying the substitute member.
31 . A method for warning of a potential adverse drug event according to level of severity, which comprises:
a) entering a patient identifier on a graphical user interface;
b) entering, retrieving or modifying a patient treatment regimen, wherein said patient treatment regimen comprises a list of any drugs, substances, genotypes, phenotypes, or clinical factors associated with said patient identifier;
c) identifying a victim-culprit interaction that defines a first interaction pair from said list, wherein said first interaction pair comprises one victim and one culprit which interact to produce a change in activity of the victim of the pair;
d) predicting a level of severity of the victim-culprit interaction according to an algorithm for calculating a change in patient exposure to the victim;
e) searching said database for any record of a clinical report of a documented interaction between said victim and said culprit and ranking said documented interaction according to level of severity; and,
f) for any interaction pair having either a predicted level of severity or a documented level of severity that is clinically significant on said graphical user interface, graphically displaying a warning indicating said level of severity;
g) updating said warning if said list is modified; and
further wherein said method is implemented on a computerized network, said network comprising a computer or server having a first software engine in digital communication with said graphical user interface, at least one database, and computer-executable instructions for implementing said method when performing operations on said list.
32 . The method of claim 31 , wherein said change in patient exposure is calculated by multiplying an intensity factor (INTX) associated with the intensity of the interaction between said first culprit and said first victim times a fraction (R 1/1-n ) indicative of the fraction of the metabolism or transport modulated by said first culprit.
33 . The method of claim 31 , wherein said method is repeated for all interaction pairs on said list, whereby a plurality of warnings may be caused to be displayed.
34 . The method of claim 33 , wherein the change in patient exposure for any one victim having a plurality of interaction pairs associated with a plurality of culprits acting thereon is obtained by multiplying an intensity factor (INTX) associated with the intensity of the interaction between said any one victim and each culprit times a fraction (R 1/1-n ) of the metabolism or transport of the any one victim modulated by each culprit, and then summing the changes for said plurality of interaction pairs.
35 . The method of claim 33 , which further comprises: for each interaction pair, searching said database for any note or notes of clinical relevance and displaying said note or notes according to a hierarchical listing of potential importance.
36 . The method of claim 35 , comprising displaying any note or notes for an interaction pair associated with an additive side effect or drug:drug interaction not directly linked to a genetic polymorphism.
37 . The method of claim 36 , wherein said interaction pair comprises a drug pair causing QT/QTc prolongation or slowing the heart rate.
38 . The method of claim 35 , wherein said warnings and notes are displayed according to the following priority ranking:
i) a major interaction documented in a clinical report;
ii) a minor interaction documented in a clinical report;
iii) a major interaction predicted by said algorithm; and,
iv) a lesser interaction predicted by said algorithm.
39 . A method for analyzing an adverse drug reaction having a pharmacogenetic basis, which comprises:
a) entering a patient identifier and a patient treatment regimen on a graphical user interface, said patient treatment regimen comprising a first interaction pair, wherein said first interaction pair is defined by a victim and a culprit which interact to produce a change in metabolism of said victim by at least one metabolic pathway;
b) entering a postulated phenotype associated with an adverse reaction involving said interaction pair;
c) calculating a level of severity of the interaction therebetween according to a predictive algorithm for calculating a change point score (CP) for said victim, wherein said predictive algorithm is implemented on a computerized network, said network comprising a first software engine, at least one database, and computer-executable instructions for implementing said algorithm when provided with said at least one said interaction pair, said network having a digital connection to said user interface;
d) displaying said predicted level of severity on said graphical user interface; and,
e) if said predicted interaction and predicted level of severity of the interaction correlates with the clinical features of an adverse drug reaction having a pharmacogenetic basis, then ordering a genetic test that is confirmatory for the postulated phenotype.
40 . The method of claim 39 , which further comprises displaying a hyperlink for ordering said confirmatory genetic test from a preferred supplier of genetic testing.