Search

Genome-wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression-free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab-paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease-free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.

Methadone is a mu (μ) opioid receptor agonist used clinically in adults and children to manage opioid use disorder, neonatal abstinence syndrome, and acute and chronic pain. It is typically marketed as a racemic mixture of R- and S-enantiomers. R-methadone has 30-to 50-fold higher analgesic potency than S-methadone, and S-methadone has a greater adverse effect (prolongation) on the cardiac QTc interval. Methadone undergoes stereoselective metabolism. CYP2B6 is the primary enzyme responsible for catalyzing the metabolism of both enantiomers to the inactive metabolites, S- and R-2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (S- and R-EDDP). Genetic variation in the CYP2B6 gene has been investigated in the context of implications for methadone pharmacokinetics, dose, and clinical outcomes. Most CYP2B6 variants result in diminished or loss of CYP2B6 enzyme activity, which can lead to higher plasma methadone concentrations (affecting S- more than R-methadone). However, the data do not consistently indicate that CYP2B6-based metabolic variability has a clinically significant effect on methadone dose, efficacy, or QTc prolongation. Expert analysis of the published literature does not support a change from standard methadone prescribing based on CYP2B6 genotype (updates at www.cpicpgx.org)., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics © 2024 American Society for Clinical Pharmacology and Therapeutics.)

In this study, we investigated the combined influence of pregnancy and genetic polymorphisms on efavirenz pharmacokinetics in cervicovaginal fluid (CVF) of women receiving antiretroviral therapy. Women receiving efavirenz-containing antiretroviral therapy were recruited from two hospitals in Nigeria during 2017-2020. Sparse CVF and plasma samples were obtained during pregnancy to assess the possible association between drug concentration and CYP2B6 polymorphisms (stage I). Participants were stratified into three CYP2B6 516G>T (rs3745274) genotype groups and re-enrolled for intensive pharmacokinetic sampling (stage II). Overall, 159 women (142 pregnant and 12 postpartum) contributed samples in stage I (88 CVF, 81 plasma and 73 paired). CYP2B6 516G>T (rs3745274) remained independently associated with log 10 efavirenz CVF concentration during pregnancy after adjusting for plasma concentration, with β (Log 10 efavirenz concentration, 95%CI) of 0.204 (0.027, 0.382), P = 0.025). Median (IQR) efavirenz C min in CVF during pregnancy (n = 12) vs. postpartum (n = 12) was 243 ng/mL (168-402) vs. 447 ng/mL (159-974), C max was 1,031 ng/mL (595-1,771) vs. 1,618 ng/mL (675-2,695), and AUC 0-24h was 16,465 ng.h/mL (9,356-30,417) vs. 30,715 ng.h/mL (10,980-43,714). CVF-to-plasma AUC ratio was 0.36 during pregnancy and 0.46 postpartum. Upon stratification, efavirenz clearance during pregnancy was 57.9% higher than postpartum in patients with the CYP2B6 516GT genotype; the AUC 0-24h and C max were 33.8% and 8.6% lower, respectively. Efavirenz C min in CVF exceeded the protein binding-adjusted IC 90 (PBIC 90 ) of 126 ng/mL during pregnancy and postpartum. Efavirenz is well distributed into the CVF; both pregnancy and CYP2B6 polymorphisms affect the extent of exposure., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems., (© 2024 The Author(s). Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Genetic polymorphisms in drug metabolizing enzymes and drug-drug interactions are major sources of inadequate drug exposure and ensuing adverse effects or insufficient responses. The current challenge in assessing drug-drug gene interactions (DDGIs) for the development of precise dose adjustment recommendation systems is to take into account both simultaneously. Here, we analyze the static models of DDGI from in vivo data and focus on the concept of phenoconversion to model inhibition and genetic polymorphisms jointly. These models are applicable to datasets where pharmacokinetic information is missing and are being used in clinical support systems and consensus dose adjustment guidelines. We show that all such models can be handled by the same formal framework, and that models that differ at first sight are all versions of the same linear phenoconversion model. This model includes the linear pharmacogenetic and inhibition models as special cases. We highlight present challenges in this endeavor and the open issues for future research in developing DDGI models for recommendation systems., (© 2024 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The Department of Veterans Affairs (VA) utilizes a pharmacogenomic (PGx) program that analyzes specific "pharmacogenes." This study evaluates the effect that pharmacogenes may have on prevalence of polypharmacy. This retrospective cohort study included patients with VA prescriptions who underwent PGx testing. We quantified prescriptions active or recently expired at the time of PGx testing. We constructed two co-primary polypharmacy (≥10 medications) end points: (i) based on all medications and (ii) requiring that at least one medication was affected by a pharmacogene of interest. Pharmacogenes and actionable phenotypes of interest included poor and ultrarapid metabolizers for CYP2D6, CYP2C9, and CYP2C19 and intermediate and normal metabolizers for CYP3A5. Patients were classified as having 0, 1, and 2+ total phenotypes across all genes. Of the 15,144 patients screened, 13,116 met eligibility criteria. Across phenotype cohorts, there was no significant association with polypharmacy using all medications, number of total medications, or number of medications affected by phenotypes. However, there was a significant difference in patients with polypharmacy prescribed ≥1 medication impacted by PGx across phenotype groups: 2,514/4,949 (51%), 1,349/2,595 (52%), 204/350 (58%) (P = 0.03, OR 1.31, 95% CI 1.02-1.67). The median number of medications affected by PGx phenotypes with ≥1 PGx-impacted medication across phenotype groups was a median of 0 (IQR 0, 0), 0 (IQR 0, 0), and 1 (IQR 0, 1) (P < 0.001). In patients prescribed ≥1 medication impacted by PGx, those with more actionable pharmacogenomic phenotypes were more likely to meet polypharmacy criteria., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA.)

The first-line treatment of hyperuricemia, which causes gout, is allopurinol. The allopurinol response is highly variable, with many users failing to achieve target serum uric acid (SUA) levels. No genome-wide association study (GWAS) has examined the genetic factors affecting allopurinol effectiveness. Using 2,027 subjects in Kaiser Permanente's Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort, we conducted a GWAS of allopurinol-related SUA reduction, first in the largest ethnic group, non-Hispanic white (NHW) subjects, and then in a stratified transethnic meta-analysis. ABCG2, encoding the efflux pump BCRP, was associated with SUA reduction in NHW subjects (P = 2 × 10(-8) ), and a missense allele (rs2231142) was associated with a reduced response (P = 3 × 10(-7) ) in the meta-analysis. Isotopic uptake studies in cells demonstrated that BCRP transports allopurinol and genetic variants in ABCG2 affect this transport. Collectively, this first GWAS of allopurinol response demonstrates that ABCG2 is a key determinant of response to the drug.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for HLA-B Genotype and Abacavir Dosing were originally published in April 2012. We reviewed recent literature and concluded that none of the evidence would change the therapeutic recommendations in the original guideline; therefore, the original publication remains clinically current. However, we have updated the Supplementary Material online and included additional resources for applying CPIC guidelines to the electronic health record. Up-to-date information can be found at PharmGKB (http://www.pharmgkb.org).

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Methadone and buprenorphine/naloxone are opioid agonist therapies for opioid use disorder treatment. Genetic factors contribute to individual differences in opioid response; however, little is known regarding genetic associations with clinical outcomes in people receiving opioid agonist therapies. Participants diagnosed with opioid use disorder, principally consisting of prescription opioids (licit or illicit), were randomized to methadone or buprenorphine/naloxone for 24 weeks of daily treatment (NCT03033732). Urine was collected at 12 biweekly study visits and analyzed for non-treatment opioids. Variants in genes involved in methadone metabolism (CYP2B6, CYP2C19, and CYP3A4), buprenorphine metabolism (CYP3A4 and UGT2B7), and μ-opioid receptor function (OPRM1) were genotyped and analyzed for their association with the number of non-treatment opioid-free urine screens. Primary analyses focused on the last 12 weeks (6 study visits, post-titration) of treatment among those reporting White ethnicity. Additional sensitivity and exploratory analyses were performed. Among methadone-treated participants (n = 52), the OPRM1 rs1799971 AA genotype (vs. G-genotypes, i.e., having one or two G alleles) was associated with greater opioid-free urine screens (incidence rate ratio = 5.24, 95% confidence interval (CI) = 2.43-11.26, P = 0.000023); longitudinal analyses showed a significant genotype-by-time interaction over the full 24 weeks (12 study visits, β = -0.28, 95% CI = -0.45 to -0.11, P = 0.0015). Exploratory analyses suggest an OPRM1 rs1799971 genotype effect on retention. No evidence of association was found between other genetic variants, including in metabolic variants, and non-treatment opioid-free urine screens in the methadone or buprenorphine/naloxone arms. Those with the OPRM1 rs1799971 G-genotypes may have a poorer response to methadone maintenance treatment, an effect that persisted through 24 weeks of treatment., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The objective of this study was to characterize clinician response following standardization of pharmacogenetic (PGx) clinical decision support alerts at University of Florida (UF) Health. A retrospective analysis of all PGx alerts that fired at a tertiary academic medical center from August 2020 through May 2022 was performed. Alert acceptance rate was calculated and compared across six gene-drug pairs, patient care setting, and clinician specialty. The disposition of the triggering medication was compared with the alert response and evaluated for congruence. There were a total of 818 alerts included for analysis of alert response, 557 alerts included in acceptance rate calculations, and 392 alerts with sufficient information to assess clinical response. The overall acceptance rate was 63%. The alert response and clinical response were congruent for 47% of alerts. Alert response was influenced by the triggering gene-drug pair, clinician specialty, patient care setting, and specialty of the provider who initially ordered the PGx test. Clinical response was mostly incongruent with alert response. Alert acceptance is influenced by the triggering gene-drug pair, clinician specialty, and care setting. Alert response is not a reliable surrogate marker for clinical action. Any future research into the impact of clinical decision support (CDS) alerts should focus on clinical response rather than alert response. Given the reliance on CDS alerts to enhance uptake of PGx, it is worthwhile to further investigate their impact on prescribing and patient outcomes., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Precision medicine has evolved from the application of pharmacogenetic biomarkers to the prospective development of targeted therapies in patients with specific molecular/genetic subtypes of disease to truly "N-of-1" medicines targeted to very small numbers of patients - in some cases, a single identified patient. This latter iteration of precision medicine presents unprecedented opportunities for patients with severe, life-threatening, or life-limiting diseases. At the same time, these modalities present complex scientific, clinical, and regulatory challenges. To realize the promise of individualized medicines, a multistakeholder approach to streamlining medical diagnoses, advancing the technologies that enable development of these therapeutic modalities, and re-envisioning collaborative environments for access and evidence generation is of critical importance. Herein, we highlight some of these challenges and opportunities., (© 2023 American Society for Clinical Pharmacology and Therapeutics. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Aminoglycoside antibiotic exposure can result in ototoxicity and irreversible hearing loss among individuals that harbor the m.1555A>G variant in the mitochondrial 12S rRNA gene, MT-RNR1. Importantly, pre-emptive m.1555A>G screening has been shown to reduce the prevalence of pediatric aminoglycoside-induced ototoxicity; however, professional guidelines to support and guide post-test pharmacogenomic counseling in this context are not currently available. This Perspective highlights key issues with delivering MT-RNR1 results, including longitudinal familial care considerations and communicating m.1555A>G heteroplasmy., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Using pharmacogenetics (PGx) to inform clinical decision making can benefit patients but clinical use of PGx testing has been limited. Existing genetics data obtained in the course of research could be used to identify patients who are suspected, but have not yet been confirmed, to carry clinically actionable genotypes, in whom confirmatory genetic testing could be conducted for highly efficient PGx implementation. Herein, we demonstrate that it is regulatorily and technically feasible to implement PGx by identifying suspected carriers of actionable genotypes within an institutional genetics data repository and conduct confirmatory PGx testing immediately prior to that patient receiving the PGx-relevant drug, using a case study of DPYD testing prior to fluoropyrimidine chemotherapy. In 2 years since launching this program, ~ 3,000 suspected DPYD carriers have been passively monitored and one confirmed DPYD carrier was prevented from receiving unacceptably toxic fluoropyrimidine treatment, for minimal cost and effort. Now that we have demonstrated the feasibility of this strategy, we plan to transition to PGx panel testing and expand implementation to other genes and drugs for which the evidence of clinical benefit of PGx-informed treatment is high but PGx testing is not generally conducted. This highly efficient implementation process will maximize the clinical benefits of testing and could be explored at other institutions that have research-only genetic data repositories to expand the number of patients who benefit from PGx-informed treatment while we continue to work toward wide-scale adoption of PGx testing and implementation., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is associated with development of acute hemolytic anemia in the setting of oxidative stress, which can be caused by medication exposure. Regulatory agencies worldwide warn against the use of certain medications in persons with G6PD deficiency, but in many cases, this information is conflicting, and the clinical evidence is sparse. This guideline provides information on using G6PD genotype as part of the diagnosis of G6PD deficiency and classifies medications that have been previously implicated as unsafe in individuals with G6PD deficiency by one or more sources. We classify these medications as high, medium, or low to no risk based on a systematic review of the published evidence of the gene-drug associations and regulatory warnings. In patients with G6PD deficiency, high-risk medications should be avoided, medium-risk medications should be used with caution, and low-to-no risk medications can be used with standard precautions, without regard to G6PD phenotype. This new document replaces the prior Clinical Pharmacogenetics Implementation Consortium guideline for rasburicase therapy in the context of G6PD genotype (updates at: www.cpicpgx.org)., (© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.)

Clinical decision support (CDS) is often cited as an essential part of pharmacogenomics (PGx) implementations. A multitude of strategies are available; however, it is unclear which strategies are effective and which metrics are used to quantify clinical utility. The objective of this scoping review was to aggregate previous studies into a cohesive depiction of the current state of PGx CDS implementations and identify areas for future research on PGx CDS. Articles were included if they (i) described electronic CDS tools for PGx and (ii) reported metrics related to PGx CDS. Twenty of 3,449 articles were included and provided data on PGx CDS metrics from 15 institutions, with 93% of programs located at academic medical centers. The most common tools in CDS implementations were interruptive post-test alerts. Metrics for clinical response and alert response ranged from 12-73% and 21-98%, respectively. Few data were found on changes in metrics over time and measures that drove the evolution of CDS systems. Relatively few data were available regarding support of optimal approaches for PGx CDS. Post-test alerts were the most widely studied approach, and their effectiveness varied greatly. Further research on the usability, effectiveness, and optimization of CDS tools is needed., (© 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes-derived from activity scores-were examined across multiple sub-Saharan African populations based on bioinformatics analysis of 961 high-depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high-fidelity Single-Molecule Real-Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty-seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population-specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora., (© 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Oral anticoagulants (OACs) are commonly used to reduce the risk of venous thromboembolism and the risk of stroke in patients with atrial fibrillation. Endorsed by the American Heart Association, American College of Cardiology, and the European Society of Cardiology, direct oral anticoagulants (DOACs) have displaced warfarin as the OAC of choice for both conditions, due to improved safety profiles, fewer drug-drug and drug-diet interactions, and lack of monitoring requirements. Despite their widespread use and improved safety over warfarin, DOAC-related bleeding remains a major concern for patients. DOACs have stable pharmacokinetics and pharmacodynamics; however, variability in DOAC response is common and may be attributed to numerous factors, including patient-specific factors, concomitant medications, comorbid conditions, and genetics. Although DOAC randomized controlled trials included patients of varying ages and levels of kidney function, they failed to include patients of diverse ancestries. Additionally, current evidence to support DOAC pharmacogenetic associations have primarily been derived from European and Asian individuals. Given differences in genotype frequencies and disease burden among patients of different biogeographic groups, future research must engage diverse populations to assess and quantify the impact of predictors on DOAC response. Current under-representation of patients from diverse racial groups does not allow for proper generalization of the influence of clinical and genetic factors in relation to DOAC variability. Herein, we discuss factors affecting DOAC response, such as age, sex, weight, kidney function, drug interactions, and pharmacogenetics, while offering a new perspective on the need for further research including frequently excluded groups., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Most pharmacogenetic research is conducted in adult, non-pregnant populations of European ancestry. Study of more diverse and special populations is necessary to validate findings and improve health equity. However, there are significant barriers to recruitment of diverse populations for genetic studies, such as mistrust of researchers due to a history of unethical research and ongoing social inequities. Engaging communities and understanding community members' perspectives may help to overcome these barriers and improve research quality. Here, we highlight one method for engaging communities, the Community Engagement Studio (CES), a consultative session that allows researchers to obtain guidance and feedback based on community members' lived experiences. We also provide an example of its use in pharmacogenetic studies. In designing a survey study of knowledge and attitudes around pharmacogenetic testing among children with chronic conditions and pregnant individuals, we sought input from diverse community stakeholders through CESs at Vanderbilt University Medical Center. We participated in two CESs with community stakeholders representing study target populations. Our goals were to learn specific concerns about pharmacogenetic testing and preferred recruitment strategies for these communities. Concerns were expressed about how genetic information would be used beyond the immediate study. Participants emphasized the importance of clarity and transparency in communication to overcome participation hesitancy and mistrust of the study team. Recruitment strategy recommendations ranged from informal notices posted in healthcare settings to provider referrals. The CES enabled us to modify our recruitment methods and research materials to better communicate with populations currently under-represented in pharmacogenetics research., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

Intravenous busulfan doses are often personalized to a target plasma exposure (targeted busulfan) using an individual's busulfan clearance (BuCL). We evaluated whether BuCL could be predicted by a predose plasma panel of 841 endogenous metabolomic compounds (EMCs). In this prospective cohort of 132 hematopoietic cell transplantation (HCT) patients, all had samples collected immediately before busulfan administration (preBU) and 96 had samples collected 2 weeks before busulfan (2-week-preBU). BuCL was significantly associated with 37 EMCs after univariate linear regression analysis and controlling for false discovery (< 0.05) in the 132 preBU samples. In parallel, with preBU samples, we included all 841 EMCs in a least absolute shrinkage and selection operator-penalized regression which selected 13 EMCs as predominantly associated with BuCL. Then, we constructed a prediction model by estimating coefficients for these 13 EMCs, along with sex, using ordinary least-squares. When the resulting linear prediction model was applied to the 2-week-preBU samples, it explained 40% of the variation in BuCL (adjusted R 2  = 0.40). Pathway enrichment analysis revealed 18 pathways associated with BuCL. Lysine degradation followed by steroid biosynthesis, which aligned with the univariate analysis, were the top two pathways. BuCL can be predicted before busulfan administration with a linear regression model of 13 EMCs. This pharmacometabolomics method should be prioritized over use of a busulfan test dose or pharmacogenomics to guide busulfan dosing. These results highlight the potential of pharmacometabolomics as a precision medicine tool to improve or replace pharmacokinetics to personalize busulfan doses., (© 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC)., (© 2022 The Authors. Clinical Pharmacology & Therapeutics © 2022 American Society for Clinical Pharmacology and Therapeutics.)

The objective of this study was to evaluate the evidence on cost-effectiveness of pharmacogenetic (PGx)-guided treatment for drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A systematic review was conducted using multiple biomedical literature databases from inception to June 2021. Full articles comparing PGx-guided with nonguided treatment were included for data extraction. Quality of Health Economic Studies (QHES) was used to assess robustness of each study (0-100). Data are reported using descriptive statistics. Of 108 studies evaluating 39 drugs, 77 (71%) showed PGx testing was cost-effective (CE) (N = 48) or cost-saving (CS) (N = 29); 21 (20%) were not CE; 10 (9%) were uncertain. Clopidogrel had the most articles (N = 23), of which 22 demonstrated CE or CS, followed by warfarin (N = 16), of which 7 demonstrated CE or CS. Of 26 studies evaluating human leukocyte antigen (HLA) testing for abacavir (N = 8), allopurinol (N = 10), or carbamazepine/phenytoin (N = 8), 15 demonstrated CE or CS. Nine of 11 antidepressant articles demonstrated CE or CS. The median QHES score reflected high-quality studies (91; range 48-100). Most studies evaluating cost-effectiveness favored PGx testing. Limited data exist on cost-effectiveness of preemptive and multigene testing across disease states., (© 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)