Multisite evaluation of institutional processes and implementation determinants for pharmacogenetic testing to guide antidepressant therapy.

There is growing interest in utilizing pharmacogenetic (PGx) testing to guide antidepressant use, but there is lack of clarity on how to implement testing into clinical practice. We administered two surveys at 17 sites that had implemented or were in the process of implementing PGx testing for antidepressants. Survey 1 collected data on the process and logistics of testing. Survey 2 asked sites to rank the importance of Consolidated Framework for Implementation Research (CFIR) constructs using best-worst scaling choice experiments. Of the 17 sites, 13 had implemented testing and four were in the planning stage. Thirteen offered testing in the outpatient setting, and nine in both outpatient/inpatient settings. PGx tests were mainly ordered by psychiatry (92%) and primary care (69%) providers. CYP2C19 and CYP2D6 were the most commonly tested genes. The justification for antidepressants selected for PGx guidance was based on Clinical Pharmacogenetics Implementation Consortium guidelines (94%) and US Food and Drug Administration (FDA; 75.6%) guidance. Both institutional (53%) and commercial laboratories (53%) were used for testing. Sites varied on the methods for returning results to providers and patients. Sites were consistent in ranking CFIR constructs and identified patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and the identification of champions as most important for implementation. Sites deployed similar implementation strategies and measured similar outcomes. The process of implementing PGx testing to guide antidepressant therapy varied across sites, but key drivers for successful implementation were similar and may help guide other institutions interested in providing PGx-guided pharmacotherapy for antidepressant management

Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems.

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing

Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients

Importance: Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective: To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, setting, and participants: This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures: Prescription of 38 level A medications based on electronic health records. Main outcomes and measures: Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results: Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and relevance: These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants

Patient-Level Exposure to Actionable Pharmacogenomic Medications in a Nationally Representative Insurance Claims Database

Background: The prevalence of exposure to pharmacogenomic medications is well established but little is known about how long patients are exposed to these medications. Aim: Our objective was to describe the amount of exposure to actionable pharmacogenomic medications using patient-level measures among a large nationally representative population using an insurance claims database. Methods: Our retrospective cohort study included adults (18+ years) from the IQVIA PharMetrics® Plus for Academics claims database with incident fills of 72 Clinical Pharmacogenetics Implementation Consortium level A, A/B, or B medications from January 2012 through September 2018. Patient-level outcomes included the proportion of days covered (PDC), number of fills, and average days supplied per fill over a 12-month period. Results: Over 1 million fills of pharmacogenetic medications were identified for 605,355 unique patients. The mean PDC for all medications was 0.21 (SD 0.3), suggesting patients were exposed 21% (77 days) of the year. Medications with the highest PDC (0.55–0.89) included ivacaftor, tamoxifen, clopidogrel, HIV medications, transplant medications, and statins; with the exception of statins, these medications were initiated by fewer patients. Pharmacogenomic medications were filled an average of 2.8 times (SD 3.0, range 1–81) during the year following the medication’s initiation, and the average days supplied for each fill was 22.3 days (SD 22.4, range 1–180 days). Conclusion: Patient characteristics associated with more medication exposure were male sex, older age, and comorbid chronic conditions. Prescription fill data provide patient-level exposure metrics that can further our understanding of pharmacogenomic medication utilization and help inform opportunities for pharmacogenomic testing

Feasibility of clinical pharmacist-led CYP2C19 genotyping for patients receiving non-emergent cardiac catheterization in an integrated health system

Objective: To assess the feasibility of clinical pharmacist-led CYP2C19 genotype-guided P2Y12 inhibitor antiplatelet drug therapy recommendations to cardiologists in an outpatient cardiology practice. Methods: This was a prospective, open-labeled, single-arm study conducted in an integrated healthcare delivery system between March 1, 2013 and January 23, 2014. Patients requiring non-emergent cardiac catheterization were included.  A clinical pharmacist provided interpretation and recommendations from genotyping results. The feasibility of implementing CYP2C19 genotype-guided antiplatelet therapy was assessed by the: 1) percentage of patients approached who consented to CYP2C19 genotyping, 2) percentage of patients with CYP2C19 genotyping results available prior to cardiac catheterization, and 3) percentage of clinical pharmacist CYP2C19 genotype-based antiplatelet recommendations accepted by cardiologists.Results: Of the 43 patients identified for potential recruitment, 22 of these were eligible for study enrollment and 6 (27%) patients consented and received CYP2C19 genotyping. All patients had genotyping results available prior to catheterization and all clinical pharmacists’ antiplatelet therapy recommendations were accepted by the patients’ cardiologists. Three patients had the CYP2C19 wild-type (*1/*1) genotype and the clinical pharmacist recommended clopidogrel therapy. CYP2C19 variant genotypes (i.e., *1/*2, *1/*17, and *2/*17) were found in the other three patients; alternative antiplatelet therapy was recommended for the patient with the *1/*2 genotype, while clopidogrel was recommended for those with *1/*17 and *2/*17 genotypes. Conclusion: A relatively small proportion of patients undergoing non-emergent cardiac catheterization consented to pharmacogenetic testing; however, their cardiologists were receptive to clinical pharmacists conducting such testing and providing corresponding pharmacotherapy recommendations. Future studies should identify patient barriers to pharmacogenetic testing

Influence of <it>SLCO1B1 </it>and <it>CYP2C8 </it>gene polymorphisms on rosiglitazone pharmacokinetics in healthy volunteers

Abstract Polymorphisms in drug transporter genes and/or drug-metabolising enzyme genes may contribute to inter-individual variability in rosiglitazone pharmacokinetics in humans. We sought to determine the joint effects of polymorphisms in the SLCO1B1 drug transporter gene and the cytochrome P450 (CYP) 2C8-metabolising enzyme gene on rosiglitazone pharmacokinetics in healthy volunteers. Healthy Caucasian subjects were prospectively enrolled on the basis of SLCO1B1 521 T > C genotype. Additionally, subjects were genotyped for SLCO1B1 11187 G > A, - 10499 A > C and 388 A > G polymorphisms, and the CYP2C8*3 polymorphism. SLCO1B1 haplotypes and diplotypes were computationally assigned. Rosiglitazone plasma concentrations were determined by high-performance liquid chromatography and analysed using non-compartmental methods. The study population consisted of 26 subjects, with a mean age of 33 ± 9 years, and a mean weight of 66.6 ± 11.7 kg. There were no significant differences in rosiglitazone pharmacokinetic parameters between SLCO1B1 diplotype groups. Subjects with the CYP2C8*1/*3 genotype (n = 7), however, had significantly lower rosiglitazone area under the plasma concentration-time curve (AUC) and significantly higher rosiglitazone oral clearance, compared with CYP2C8 wild-type homozygotes (n = 19). Stepwise linear regression analysis revealed that CYP2C8 genotype (p = 0.006) and weight (p = 0.022) were significant predictors of rosiglitazone AUC (overall p = 0.002; R2 = 41.6 per cent). We concluded that polymorphisms in the CYP2C8 drug-metabolising enzyme gene, but not the SLCO1B1 drug transporter gene, significantly influence rosiglitazone disposition in humans. Future studies examining the influence of CYP2C8 genotypes and haplotypes on thiazolidinedione disposition and response in patients with type 2 diabetes are warranted.</p