Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2B6 Genotype and Methadone Therapy.

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).

A Genetics-Focused Lens on Social Constructs in Pharmacy Education.

OBJECTIVE: Incorporating diversity, equity, inclusion, and anti-racism principles into clinical and didactic education is essential because each influence cognitive and affective attitudes in pharmacy practice. Educators must learn from the past to enlighten the future. For example, race is a social construct, not a biological construct. However, it persistently acts as a surrogate for determining medical diagnoses and treatment. FINDINGS: Precision medicine and pharmacogenomics can serve as a basis for deconstructing social constructs surrounding race and other social determinants of health. SUMMARY: In this review, the authors highlight why using race in health education will lead to less-than-optimal clinical decisions and discuss best practices for incorporating diversity, equity, inclusion, and anti-racism into health education from a pharmacogenomic-based perspective.

The Intersection of Professional Identity Formation, Bias, and Marginalized Identities.

OBJECTIVES: The objective of this integrative review is to call attention to the limited published literature on professional identity formation (PIF) in students who hold marginalized identities and to promote more inclusive PIF models. FINDINGS: A person's identity is complicated and PIF is a dynamic and continuous lifelong process. A foundational component to PIF is for students to integrate their developing professional identity with their existing selves. Most PIF theoretical frameworks used in health education were created with a dominant culture lens and during a time when most professionals in practice were cisgendered, White, and/or male. These frameworks do not consider ways in which PIF may differ in learners who hold marginalized identities nor the influence that their marginalized identities may have on facilitators and barriers to their PIF journeys. SUMMARY: PIF is a growing area of focus in pharmacy education and scholarship. To effectively support PIF for each member of a diverse student body, pharmacy educators must recognize the limitations of existing PIF theoretical frameworks owing to the historical exclusion of considerations of students' and practitioners' marginalized identities as a layer of professional identity, especially in the context of historical injustices. As members of the pharmacy Academy begin or continue to explore PIF in pharmacy education, they must be mindful and intentional about how they account for the impact that students' marginalized identities may have on their PIF.

Advancing Pharmacogenomics-Based Care Through Interprofessional Education.

As genomic medicine becomes increasingly complex, pharmacists need to work collaboratively with other healthcare professionals to provide genomics-based care. The core pharmacist competencies in genomics were recently updated and mapped to the entrustable professional activities (EPAs). The new competency that is mapped to the "Interprofessional Team Member" EPA domain emphasizes the role of pharmacists as the pharmacogenomics experts in an interprofessional healthcare team. Interprofessional education (IPE) activities involving student pharmacists and students from other healthcare disciplines are crucial to prepare student pharmacists for a team-based approach to patient-centered care. This commentary discusses the pharmacogenomics-focused IPE activities implemented by 3 programs, the challenges faced, and the lessons learned. It also discusses strategies to develop pharmacogenomics-focused IPE activities based on existing resources. Developing pharmacogenomics-focused IPE activities will help prepare pharmacy graduates with the knowledge, skills, and attitudes to lead collaborative, interprofessional teams in the provision of pharmacogenomics-based care, consistent with the standards described in the genomics competencies for pharmacists.

Gender-gap in randomized clinical trials reporting mortality in the perioperative setting and critical care: 20 years behind the scenes.

Background: Women researchers might experience obstacles in academic environments and might be underrepresented in the authorship of articles published in peer-reviewed journals. Material and Methods: This is a cross-sectional analysis of female-led RCTs describing all interventions reducing mortality in critically ill and perioperative patients from 1981 to December 31, 2020. We searched PubMed/MEDLINE and EMBASE with the keywords RCTs and mortality. The gender of the first author was extracted and descriptive analysis was performed including the year of publication, impact factor, country of the first author, and methodological aspects. Results: We analyzed 340 RCTs, of which 42 (12%) were led by female researchers. The presence of women increased from 8% (14/172) until 2010 up to 17% (28/168) in 2010 and beyond. The United States, the United Kingdom, and Brazil were the main countries of origin of female researchers. Women authors conducted mainly single-center and single-nation studies as compared to male authors. The median impact factor of the target journal was 6 (3-27) in women vs. 7 (3-28) in men, with a p-value of 0.67; Critical Care Medicine, JAMA, and The New England Journal of Medicine were the most frequent target journals for both women and men. Conclusion: In the last 40 years, only one out of eight RCTs had a woman as the first author but the presence of women increased up to 17% by 2010 and beyond. The impact factor of publication target journals was high and not different between genders.

Improving team dynamics for project based learning in pharmacy: A multimodal approach.

BACKGROUND AND PURPOSE: Students taking a research elective with project-based course components have shown aversion to group activities. We aimed to minimize group participation hesitancy and give students autonomy in choice of team formation approach in order to examine the effects of team formation approaches on successful team dynamics. EDUCATIONAL ACTIVITY AND SETTING: Learners chose either a student self-selected (SS) or an instructor randomized (IR) team formation approach for two activities (a brief intervention role-play and a review of reviews research symposia presentation). Group development for the different team approaches was studied using the Tuckman model. Using this model, team dynamics was evaluated over five stages of group development: forming, norming, storming, performing, and adjourning. Student reports for each of the phases were evaluated using a project evaluation rubric. For the adjourning phase we used an open-ended survey embedded in the course learning management system. Free text answers from open-ended questions were analyzed for themes related to team dynamics concepts. FINDINGS: Students rated their satisfaction with team performance higher for SS than for IR teams. In terms of individual learning and satisfaction with individual's roles and tasks, they indicated greater satisfaction with the IR approach. SUMMARY: Team formation methods impacted group dynamics and individual attitudes with favorable team dynamics leading to better individual task and overall team performance. Higher team performance corresponds to higher grades for group projects and for courses with group projects, favorable team dynamics could impact students' evaluation of the course.

Pharmacists Leading the Way to Precision Medicine: Updates to the Core Pharmacist Competencies in Genomics.

Genomics is becoming an increasingly important part of health care, and pharmacists are well-positioned to be practice-based leaders in pharmacogenomics and precision medicine. Competencies available through the Genetics/Genomics Competency Center provide a framework for pharmacogenomics instruction in both pharmacy school curricula and continuing education programs. Given the significant advancements in pharmacogenomics over the past decade, the 2019-2020 American Association of Colleges of Pharmacy Pharmacogenomics Special Interest Group updated the pharmacist competencies. The process used a systematic approach which included mapping pharmacogenomics-specific competencies to the entrustable professional activities for pharmacists and seeking consensus from key stakeholders. The result is an expansion to 30 competencies that reflect the contemporary roles pharmacists play in the application of pharmacogenomics in clinical practice. When implemented into curricula, these competencies will ensure that learners are "practice ready" to integrate pharmacogenomics into patient care. Additional postgraduate training is needed for advanced roles in pharmacogenomics implementation, education, and research.

Case Study 1: Practical Considerations with Experimental Design and Interpretation.

This chapter deals with practical considerations on key issues such as choosing an enzyme source, determining linear conditions, and choosing appropriate substrate and organic solvent concentrations. Practical solutions for working with limited resources and carrying out inhibition experiments are also addressed. Thus, after reading this chapter, the novice reader should have a better idea of how to design, develop, and interpret basic experiments using drug metabolism enzymes.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2B6 and Efavirenz-Containing Antiretroviral Therapy.

The HIV type-1 nonnucleoside reverse transcriptase inhibitor, efavirenz, is widely used to treat HIV type-1 infection. Efavirenz is predominantly metabolized into inactive metabolites by cytochrome P450 (CYP)2B6, and patients with certain CYP2B6 genetic variants may be at increased risk for adverse effects, particularly central nervous system toxicity and treatment discontinuation. We summarize the evidence from the literature and provide therapeutic recommendations for efavirenz prescribing based on CYP2B6 genotypes.

Using Personalized Medicine in the Management of Diabetes Mellitus.

Diabetes mellitus is a worldwide problem with an immense pharmacoeconomic burden. The multifactorial and complex nature of the disease lends itself to personalized pharmacotherapeutic approaches to treatment. Variability in individual risk and subsequent development of diabetes has been reported in addition to differences in response to the many oral glucose lowering therapies currently available for diabetes pharmacotherapy. Pharmacogenomic studies have attempted to uncover the heritable components of individual variability in risk susceptibility and response to pharmacotherapy. We review the current pharmacogenomics evidence as it relates to common oral glucose lowering therapies and how they can be utilized in the management of polygenic and monogenic forms of diabetes. Evidence supports the use of genetic testing and personalized approaches to the treatment of monogenic diabetes of the young. The data are not as robust for the current application of pharmacogenetic approaches to the treatment of polygenic type 2 diabetes mellitus, but there are suggestions as to future applications in this regard. We reviewed pertinent primary literature sources as well as current evidence-based guidelines on diabetes management.

Genetic determinants of variability in warfarin response after the dose-titration phase.

OBJECTIVES: Genetic factors contribute considerably toward variability in warfarin dose requirements and are important in the dose-titration phase; their effects on the stability of anticoagulation later in therapy are not known. METHODS: Using deidentified electronic medical records linked to a DNA-biobank, we studied 140 African-Americans and 943 European-Americans after the warfarin dose-titration phase. We genotyped 12 single nucleotide polymorphisms in genes (CYP2C9, VKORC1, CYP4F2, GGCX, EPHX1, CALU) associated with altered warfarin dose requirements and tested their associations with international normalized ratio variability (INRVAR) and percent time in therapeutic range in European-Americans and African-Americans. RESULTS: One allele copy of rs2108622 in CYP4F2 was associated with a 15% [95% confidence interval (CI): 1-26, P=0.03] decrease in the median INRVAR in European-Americans. In African-Americans, GGCX variants rs11676382 and rs699664 were associated with 4.16-fold (95% CI: 1.45-11.97, P=0.009) and 1.50-fold (95% CI: 1.07-2.08, P=0.02) changes in the median INRVAR per variant allele copy, respectively; rs11676382 was also significantly associated with a 23.19% (95% CI: 5.89-40.48, P=0.01) decrease in time in therapeutic range. The total variation in INRVAR explained by both clinical factors and rs2108622 was 5.2% for European-Americans. In African-Americans, the inclusion of GGCX variants rs11676382 and rs699664, and the CYP2C9*8 variant rs7900194 explained ∼29% of the variation in INRVAR. CONCLUSION: The stability of anticoagulation after the warfarin dose-titration phase is differentially affected by variants in CYP4F2 in European-Americans and GGCX loci in African-Americans.

Genetic variation in the UGT1A locus is associated with simvastatin efficacy in a clinical practice setting.

Aim: Simvastatin is a lactone prodrug that exists in equilibrium with its active hydroxyacid through a process mediated by UGT1A enzymes. The UGT1A locus has been associated with simvastatin response and disposition in humans. Therefore, we fine-mapped the UGT1A locus to identify genetic variations contributing to simvastatin disposition and response variability. Methods: Using de-identified electronic medical records linked to a DNA biobank, we extracted information about dose and low-density lipo-protein cholesterol (LDL-C) concentrations for patients who received more than two different doses of simvastatin. Pharmacodynamic measures of simvastatin potency and efficacy were calculated from dose-response curves (E0 = baseline LDL-C, ED50 = dose yielding 50% maximum response, and Emax = maximum decrease in LDL-C) in 1100 patients. We selected 153 polymorphisms in UGT1A1 and UGT1A3 for genotyping and conducted genotype-phenotype associations using a prespecified additive model. Results: Two variants in UGT1A1 (rs2003569 and rs12052787) were associated with Emax (p = 0.0059 and 0.031, respectively; for rs2003569 the mean Emax was 59.3 ± 23.0, 62.0 ± 22.4, and 69.7 ± 24.8 mg/dl, for patients with 0, 1 or 2 copies of the minor A allele, respectively). When stratified by race, the difference in response was greater in African-Americans than in European Americans. Rs2003569 was also negatively associated with total serum bilirubin levels (p = 7.85 × 10-5). Four rare SNPs were nominally associated with E0 and ED50. Conclusion: We identified a UGT1A1 promoter variant (rs2003569) associated with simvastatin efficacy. Original submitted 26 March 2014; Revision submitted 26 August 2014.

Case study 1. Practical considerations with experimental design and interpretation.

At some point, anyone with knowledge of drug metabolism and enzyme kinetics started out knowing little about these topics. This chapter was specifically written with the novice in mind. Regardless of the enzyme one is working with or the goal of the experiment itself, there are fundamental components and concepts of every experiment using drug metabolism enzymes. The following case studies provide practical tips, techniques, and answers to questions that may arise in the course of conducting such experiments. Issues ranging from assay design and development to data interpretation are addressed. The goal of this section is to act as a starting point to provide the reader with key questions and guidance while attempting his/her own work.

Incorporation of pharmacogenomics into routine clinical practice: the Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline development process.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug therapy. CPIC has focused initially on well-known examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the development process of the CPIC guidelines and compares this process to the Institute of Medicine's Standards for Developing Trustworthy Clinical Practice Guidelines.

Creation and Validation of an EMR-based Algorithm for Identifying Major Adverse Cardiac Events while on Statins.

Statin medications are often prescribed to ameliorate a patient's risk of cardiovascular events due in part to cholesterol reduction. We developed and evaluated an algorithm that can accurately identify subjects with major adverse cardiac events (MACE) while on statins using electronic medical record (EMR) data. The algorithm also identifies subjects experiencing their first MACE while on statins for primary prevention. The algorithm achieved 90% to 97% PPVs in identification of MACE cases as compared against physician review. By applying the algorithm to EMR data in BioVU, cases and controls were identified and used subsequently to replicate known associations with eight genetic variants. We replicated 6/8 previously reported genetic associations with cardiovascular diseases or lipid metabolism disorders. Our results demonstrated that the algorithm can be used to accurately identify subjects with MACE and MACE while on statins. Consequently, future e studies can be conducted to investigate and validate the relationship between statins and MACE using real-world clinical data.

Clinical and pharmacogenetic predictors of circulating atorvastatin and rosuvastatin concentrations in routine clinical care.

BACKGROUND: A barrier to statin therapy is myopathy associated with elevated systemic drug exposure. Our objective was to examine the association between clinical and pharmacogenetic variables and statin concentrations in patients. METHODS AND RESULTS: In total, 299 patients taking atorvastatin or rosuvastatin were prospectively recruited at an outpatient referral center. The contribution of clinical variables and transporter gene polymorphisms to statin concentration was assessed using multiple linear regression. We observed 45-fold variation in statin concentration among patients taking the same dose. After adjustment for sex, age, body mass index, ethnicity, dose, and time from last dose, SLCO1B1 c.521T>C (P<0.001) and ABCG2 c.421C>A (P<0.01) were important to rosuvastatin concentration (adjusted R(2)=0.56 for the final model). Atorvastatin concentration was associated with SLCO1B1 c.388A>G (P<0.01) and c.521T>C (P<0.05) and 4ß-hydroxycholesterol, a CYP3A activity marker (adjusted R(2)=0.47). A second cohort of 579 patients from primary and specialty care databases were retrospectively genotyped. In this cohort, genotypes associated with statin concentration were not differently distributed among dosing groups, implying providers had not yet optimized each patient's risk-benefit ratio. Nearly 50% of patients in routine practice taking the highest doses were predicted to have statin concentrations greater than the 90th percentile. CONCLUSIONS: Interindividual variability in statin exposure in patients is associated with uptake and efflux transporter polymorphisms. An algorithm incorporating genomic and clinical variables to avoid high atorvastatin and rosuvastatin levels is described; further study will determine whether this approach reduces incidence of statin myopathy.

In vivo-formed versus preformed metabolite kinetics of trans-resveratrol-3-sulfate and trans-resveratrol-3-glucuronide.

Metabolites in safety testing have gained a lot of attention recently. Regulatory agencies have suggested that the kinetics of preformed and in vivo-formed metabolites are comparable. This subject has been a topic of debate. We have compared the kinetics of in vivo-formed with preformed metabolites. trans-3,5,4'-Trihydroxystilbene [trans-resveratrol (RES)] and its two major metabolites, resveratrol-3-sulfate (R3S) and resveratrol-3-glucuronide (R3G) were used as model substrates. The pharmacokinetics (PK) of R3S and R3G were characterized under two situations. First, the pharmacokinetics of R3S and R3G were characterized (in vivo-formed metabolite) after administration of RES. Then, synthetic R3S and R3G were administered (preformed metabolite) and their pharmacokinetics were characterized. PK models were developed to describe the data. A three-compartment model for RES, a two-compartment model for R3S (preformed), and an enterohepatic cycling model for R3G (preformed) was found to describe the data well. These three models were further combined to build a comprehensive PK model, which was used to perform simulations to predict in vivo-formed metabolite kinetics. Comparisons were made between in vivo-formed and preformed metabolite kinetics. Marked differences were observed in the kinetics of preformed and in vivo-formed metabolites.