Genelex Corporation

Seattle, WA, United States

Genelex Corporation

Seattle, WA, United States

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PubMed | University Hospital of Tuebingen, Karolinska Institutet, Translational Software, Stanford University and 29 more.
Type: Journal Article | Journal: Clinical pharmacology and therapeutics | Year: 2016

This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.


Johnson S.G.,University of Colorado at Denver | Johnson S.G.,Kaiser Permanente | Gruntowicz D.,Genelex Corporation | Gruntowicz D.,VA Puget Sound Health Care System | And 3 more authors.
Journal of Managed Care Pharmacy | Year: 2015

BACKGROUND: Dual antiplatelet therapy is an established standard of care for patients with acute coronary syndrome (ACS) to reduce thrombotic risk. Reduced CYP2C19 activity impairs clopidogrel bio-activation and increases risk of adverse clinical outcomes. Patients with poor and intermediate CYP2C19 metabolizers treated with clopidogrel incur higher cardiovascular event rates, including myocardial infarction, stroke, and stent thrombosis, following ACS than patients with normal CYP2C19 function. Tests are available to identify the CYP2C19 genotype and can be used to support individualization of antiplatelet therapy. OBJECTIVE: To estimate the financial impact of CYP2C19 genotyping in a theoretical cohort of 1,000 patients with ACS, who received percutaneous coronary intervention and coronary stent implantation and were treated with clopidogrel, prasugrel, or ticagrelor in a managed care setting. METHODS: Differences in overall and average cost per patient were estimated based on the rate of CYP2C19 genotyping in a theoretical cohort of 1,000 patients. Sensitivity analysis was carried out for varying costs, adherence, and the percentage of patients treated according to genotyping results. All clinical event costs were reported in terms of 2012 U.S. dollars. The budget impact analysis used published event rates from primary literature to estimate costs of events analysis for 3 different scenarios: Scenario A, no CYP2C19 genotyping; Scenario B, 50% of patients received CYP2C19 genotyping with appropriate treatment based on genotype; and Scenario C, 100% of patients received CYP2C19 genotyping with appropriate treatment based on genotype. RESULTS: According to this model, there was no change in the market share for the 3 antiplatelet agents in Scenario A. Initial market share for clopidogrel, prasugrel, and ticagrelor was 93%, 5%, and 2%, respectively; however, use of CYP2C19 genotyping is expected to shift market share from clopidogrel to either prasugrel or ticagrelor. In Scenario B, where 50% of the patients received genotyping, clopidogrel market share was reduced to 83%, while prasugrel increased to 12.1% and ticagrelor increased to 4.9%. In Scenario C, where all patients received genotyping, clopidogrel market share was reduced to 73%, prasugrel increased to 19.3%, and ticagrelor increased to 7.7%. Total estimated cost differences when all possible patients were genotyped included annual savings of roughly $444,852. CONCLUSIONS: Important financial benefits may be realized through use of genotype-guided antiplatelet therapy to reserve prasugrel or ticagrelor use for patients with reduced CYP2C19 activity to avoid costs associated with adverse cardiac events. © 2015, Academy of Managed Care Pharmacy.


PubMed | Genelex Corporation and Washington State University
Type: Journal Article | Journal: American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists | Year: 2016

The results of a study of variant cytochrome P-450 (CYP) alleles and associated risks of drug-drug interactions (DDIs) and altered drug metabolism are reported.The records of a pharmacogenetic testing laboratory were retrospectively analyzed to identify patients tested for polymorphisms of genes coding for five CYP isozymes important in drug metabolism (CYP2D6, CYP2C9, CYP2C19, CYP3A4, and CYP3A5) over a 16-month period. Based on the results of phenotyping, the patients were categorized by expected CYP isozyme activity (e.g., normal or poor metabolizer, expresser or nonexpresser). Using proprietary Web-based software, researchers analyzed phenotyping data and medication lists submitted by patients to determine the potential for DDIs, drug-gene interactions (DGIs), and drug-drug-gene interactions (DDGIs).In the mixed-race study population of more than 22,000 male and female patients (age range, 1-108 years; mean, 60 years), phenotypes associated with alterations of CYP metabolic pathways were common. Among patients in whom phenotypes for all five isozymes of interest were determined (n = 14,578), about 93% were not categorized as normal metabolizers of all five proteins. In many cases, potential interaction threats were rated by clinicians as severe enough to warrant implementation or consideration of a medication regimen change or dose adjustment. Analysis of patient-provided medication lists indicated frequent use of medications posing DDI, DGI, or DDGI risks.In a mixed-race population of over 20,000 U.S. patients, CYP gene polymorphisms associated with DDIs and other interaction threats were prevalent, and most individuals were not categorized as normal metabolizers of all five CYP isozymes of interest.


Verbeurgt P.,Genelex Corporation | Mamiya T.,Genelex Corporation | Oesterheld J.,Genelex Corporation
Pharmacogenomics | Year: 2014

Aim: Drug-drug interactions (DDIs) are a widely recognized major cause of adverse drug reactions, but two other newly described important types of interactions also exist: drug-gene interactions (DGIs) and drug-drug-gene interactions (DDGIs). A drug-gene interaction occurs when a patient's genetic CYP450 type (e.g., CYP2D6 poor metabolizer) affects that patient's ability to clear a drug. A drug-drug-gene interaction occurs when the patient's CYP450 genotype and another drug in the patient's regimen (e.g., a CYP2D6 inhibitor) affect that individual's ability to clear a drug. Their prevalence has not been previously described. This pilot study investigates the frequency of DDIs, DGIs and DDGIs in a sample of CYP450 tested individuals. Materials & methods: The investigators conducted a retrospective analysis of 1143 individuals with known CYP2D6, CYP2C19 and CYP2C9 genotypes. Using the individuals' medication lists and YouScript®, a software tool to analyze cumulative DDIs and DGIs, the prevalence of DDI, DGI and DDGIs was analyzed. Results: A total of 1053 potential major or substantial interactions were identified in 501 individuals. DDIs accounted for 66.1% of the total interactions. The remaining 33.9% of interactions were DGIs (14.7%) and DDGIs (19.2%). When compared with DDIs alone, DGIs and DDGIs increased the total number of potentially clinically significant interactions by 51.3%. Conclusion: In the future, identifying DGIs and DDGIs may lead to a more comprehensive method of identifying individuals who are at risk for adverse drug reactions. © 2014 Future Medicine Ltd.


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.


Patent
Genelex Inc | Date: 2011-12-09

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.


Patent
Genelex Corporation | Date: 2014-01-24

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.


Patent
Genelex Inc | Date: 2011-12-09

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.


Patent
GENELEX Corporation | Date: 2012-10-08

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.


Examples described herein include methods and systems for improving accuracy of prediction of substance-factor interactions in patients. Example systems may improve drug interaction prediction for a patient taking a drug by comparing computationally predicted changes in AUC for interaction pairs involving the same metabolic pathways as the drug with change in AUC information from clinical data (e.g. clinical studies). A correction factor for use in the computational prediction may be identified which improves the accuracy of the computational predictions relative to the clinical data. The correction factor may be used to provide improved computational predictions of the change in AUC for a drug, when clinical data may be unavailable. There may be no need for a correction factor if a clinical study is available. The improved computational prediction may be used to set and/or change the amount or identity of the drug administered to a patient.

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