Real-World Impact of a Pharmacogenomics-Enriched Comprehensive Medication Management Program

SLCO1B1 Functional Variants, Bilirubin, Statin-Induced Myotoxicity, and Recent Sub-Saharan African Ancestry: A Precision Medicine Health Equity Study

Statin pharmacogenetic implementation guidelines are derived from evidence of primarily Eurocentrically biased study populations. Functional SLCO1B1 variants that are rare in these study populations have not been equitably investigated and are thus missing from guidelines. The objective of this precision medicine health equity study was to determine the clinical validity of understudied candidate functional SLCO1B1 variants common in people with 1,000 Genomes sub-Saharan African superpopulation (1KG-AFR-like) genetic similarity. We conducted our analyses using the real-world evidence of participants from three large, electronic health record-linked biobanks. We used bilirubin levels (as an endogenous substrate of organic anion transporting polypeptide [OATP1B1] function) and severe statin-induced myotoxicity phenotypes. Loss-of-function splice variant rs77271279 (P = 1.1 × 10-17) had the strongest association with elevated total bilirubin levels in Black participants (mean 84% AFR-like genetic similarity) followed by missense variant rs59502379 (P = 7.4 × 10-12) then missense variant rs4149056 (P = 6.0 × 10-5). In an exploratory subset of the Black study population who used statins (n = 77 severe statin-induced myotoxicity cases), rs59502379 (odds ratio [OR] = 2.85, 95% confidence interval [CI] 1.08-7.52), but not rs77271279 (OR = 1.75, 95% CI 0.62-4.73) was associated with myotoxicity. Sensitivity analyses in participants with >5% AFR-like genetic similarity corroborated these findings. For white participants, rs77271279 and rs59502379 were rare precluding subsequent analyses. Our findings highlight the clinical relevance for understudied SLCO1B1 variants on pharmacogenetic testing panels with a potential immediate impact on reducing the risk of severe statin-induced myotoxicity primarily in Black patients, a group historically excluded from genomic research. Future studies require larger statin user study populations with less heterogeneity by statin type.

Implementation of Integrated Clinical Pharmacogenomics Testing at an Academic Medical Center

BACKGROUND

Pharmacogenomics has demonstrated benefits for clinical care, including a reduction in adverse events and cost savings. However, barriers in expanded implementation of pharmacogenomics testing include prolonged turnaround times and integration of results into the electronic health record with clinical decision support. A clinical workflow was developed and implemented to facilitate in-house result generation and incorporation into the electronic health record at a large academic medical center.

METHODS

An 11-gene actionable pharmacogenomics panel was developed and validated using a QuantStudio 12K Flex platform. Allelic results were exported to a custom driver and rules engine, and result messages, which included a diplotype and predicted metabolic phenotype, were sent to the electronic health record; an electronic consultation (eConsult) service was integrated into the workflow. Postimplementation monitoring was performed to evaluate the frequency of actionable results and turnaround times.

RESULTS

The actionable pharmacogenomics panel covered 39 alleles across 11 genes. Metabolic phenotypes were resulted alongside gene diplotypes, and clinician-facing phenotype summaries (Genomic Indicators) were presented in the electronic health record. Postimplementation, 8 clinical areas have utilized pharmacogenomics testing, with 56% of orders occurring in the outpatient setting; 22.1% of requests included at least one actionable pharmacogene, and 67% of orders were associated with a pre- or postresult electronic consultation. Mean turnaround time from sample collection to result was 4.6 days.

CONCLUSIONS

A pharmacogenomics pipeline was successfully operationalized at a quaternary academic medical center, with direct integration of results into the electronic health record, clinical decision support, and eConsult services.

Impact of a clinical decision support system on identifying drug-related problems and making recommendations to providers during community pharmacist-led medication reviews in Ontario, Canada: A pilot study

OBJECTIVE

To evaluate the impact of a clinical decision support system (CDSS) to identify drug-related problems (DRPs) during community pharmacist medication reviews.

DESIGN

Pilot 3-phase (group), open-label study.

SETTING AND PARTICIPANTS

Two community pharmacies in Sarnia, Ontario, with pharmacists providing medication reviews to patients.

STUDY PROCEDURES

Five pharmacists participated in three phases (groups). During Phase 1, pharmacists conducted medication reviews in 25 adult patients using the usual approaches. In Phase 2, pharmacists were trained to use a CDSS to identify DRPs, and then conducted medication reviews using the tool in a different group of 25 adult patients. In Phase 3, pharmacists conducted medication reviews without the aid of the CDSS in 25 additional adult patients.

MAIN OUTCOME MEASURES

The primary outcome was recommendation to the primary care physician to alter pharmacotherapy based on medication review, assessed using mean number and frequency (yes/no) of recommendations by patient. Secondary outcomes included number of potential DRPs, actual DRPs, medication review duration time, pharmacist's perceptions of the CDSS and patient satisfaction with medication review.

RESULTS

The mean number of recommendations to primary care physicians to alter pharmacotherapy per patient in Phases 1, 2 and 3 did not differ: 1.0 (SD = I.2) versus 1.5 (1.0) versus 1.5 (1.0), respectively; p = 0.223. The percentage of patients with a pharmacy recommendation sent to physicians across the phases, however, differed: 52% versus 80% versus 88%, respectively; p = 0.010, with more in Phases 2 and 3 compared to 1. There were more potential DRPs in group 2 compared to other groups. There were no differences in actual DRPs and medication review time. Pharmacists had positive attitudes about the CDSS. Patients were generally satisfied with their medication review.

CONCLUSIONS

This small pilot study provides some preliminary evidence for performance and feasibility of a CDSS to identify DRPs that pharmacists will act on. Future research is recommended to validate these findings in a larger sample.

The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation

Pharmacogenetics promises to optimize treatment-related outcomes by informing optimal drug selection and dosing based on an individual's genotype in conjunction with other important clinical factors. Despite significant evidence of genetic associations with drug response, pharmacogenetic testing has not been widely implemented into clinical practice. Among the barriers to broad implementation are limited guidance for how to successfully integrate testing into clinical workflows and limited data on outcomes with pharmacogenetic implementation in clinical practice. The Pharmacogenomics Global Research Network Implementation Working Group seeks to engage institutions globally that have implemented pharmacogenetic testing into clinical practice or are in the process or planning stages of implementing testing to collectively disseminate data on implementation strategies, metrics, and health-related outcomes with the use of genotype-guided drug therapy to ultimately help advance pharmacogenetic implementation. This paper describes the goals, structure, and initial projects of the group in addition to implementation priorities across sites and future collaborative opportunities.

Pharmacogenetic Panel Testing: A Review of Current Practice and Potential for Clinical Implementation

Pharmacogenetics (PGx) aims to optimize drug treatment outcomes by using a patient's genetic profile for individualized drug and dose selection. Currently, reactive and pretherapeutic single-gene PGx tests are increasingly applied in clinical practice in several countries and institutions. With over 95% of the population carrying at least one actionable PGx variant, and with drugs impacted by these genetic variants being in common use, pretherapeutic or preemptive PGx panel testing appears to be an attractive option for better-informed drug prescribing. Here, we discuss the current state of PGx panel testing and explore the potential for clinical implementation. We conclude that available evidence supports the implementation of pretherapeutic PGx panel testing for drugs covered in the PGx guidelines, yet identification of specific patient populations that benefit most and cost-effectiveness data are necessary to support large-scale implementation.

Clinical and economic outcomes of a pharmacogenomics-enriched comprehensive medication management program in a self-insured employee population

Clinical and economic outcomes from a pharmacogenomics-enriched comprehensive medication management program were evaluated over 26 months in a self-insured U.S. employee population (n = 452 participants; n = 1500 controls) using propensity matched pre-post design with adjusted negative binomial and linear regression models. After adjusting for baseline covariates, program participation was associated with 39% fewer inpatient (p = 0.05) and 39% fewer emergency department (p = 0.002) visits, and with 21% more outpatient visits (p < 0.001) in the follow-up period compared to the control group. Results show pharmacogenomics-enriched comprehensive medication management can favorably impact healthcare utilization in a self-insured employer population by reducing emergency department and inpatient visits and can offer the potential for cost savings. Self-insured employers may consider implementing pharmacogenomics-enriched comprehensive medication management to improve the healthcare of their employees.

A Pharmacogenetic Panel-Based Prediction of the Clinical Outcomes in Elderly Patients with Coronary Artery Disease

Clinical annotations for the actionable pharmacogenetic variants affecting the efficacy of cardiovascular drugs have been collected, yet their impacts on elderly patients with coronary artery disease (CAD) undergoing polypharmacy remain uncertain. We consecutively enrolled 892 elderly patients (mean age 80.7 ± 5.2) with CAD and polypharmacy. All the included patients underwent genotyping for 13 variants in 10 pharmacogenes (CYP2C19, CYP2C9, CYP4F2, CYP2D6, VKORC1, SLCO1B1, APOE, ACE, ADRB1, and MTHFR), which have the clinical annotations for 12 drugs that are commonly prescribed for patients with CAD. We found that 80.3% of the elderly CAD patients had at least one drug-gene pair associated with a therapeutical drug change. After adjusting for covariates, the number of drug-gene pairs was independently associated with a decreased risk of both major cardiovascular events (MACEs) (adjusted hazard ratio [HR]: 0.803, 95% confidence interval [CI]: 0.683-0.945, p = 0.008) and all-cause mortality (adjusted HR: 0.848, 95% CI: 0.722-0.996, p = 0.045), but also with an increased risk of adverse drug reactions (ADRs) (adjusted HR: 1.170, 95% CI: 1.030-1.329, p = 0.016). The Kaplan-Meier survival curves showed that compared to patients without a drug-gene pair, a significantly lower risk of MACEs could be observed in patients with a drug-gene pair during a 4-year follow-up (HR: 0.556, 95% CI: 0.325-0.951, p = 0.013). In conclusion, the carrier status of the actionable drug-gene pair is predictive for the clinical outcomes in elderly patients with CAD and polypharmacy. Implementing early or preemptive pharmacogenetic panel-guided polypharmacy holds the potential to enhance clinical outcomes for these patients.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

The Use of Precision Medicine to Support the Precision of Clinical Decisions in care delivery

OBJECTIVES

Objective: Precision medicine uses individualized patient data, including genomic and social determinants of health SDoH), to provide optimized personalized patient treatment. In this scoping review, we summarize studies published in the last two years that reported on implementation of precision medicine in clinical decision support (CDS) related to precision medicine.

METHODS

We searched PubMed for manuscripts published in 2022 and 2023 to retrieve publications that included CDS and precision medicine keywords and Mesh terms. We reviewed the abstracts and full texts to apply the inclusion criteria that the study must have described the implementation of precision medicine related CDS within electronic health records. We extracted the domain, type of data used in CDS, target population included in the implementation from the final set of included manuscripts.

RESULTS

Our search retrieved 285 manuscripts and papers. Sixteen (16) papers met inclusion criteria after manual review of the full text. Eight of the reviewed papers studied the successful implementation of pharmacogenomics in CDS, four studies investigated the implementation of disease risk, and only one paper described the implementation of CDS integrating social determinants of health.

CONCLUSION

Our scoping review of recent literature highlighted several findings. Pharmacogenomics is the most implemented precision medicine intervention based on published studies. Few reports describing disease risk and polygenic risk scores were found and no study addressed CDS for continuous biometric monitoring. Despite the increasing attention to social determinants of health as a key predictor of health outcomes, only one CDS incorporating SDoH have been publicly reported. Regular updates to scoping reviews can investigate barriers to implementation and identify solutions.

Decoding Pharmacogenomic Test Interpretation and Application to Patient Care

Pharmacogenomics is a growing area of medicine, and pharmacists across clinical practice settings have the opportunity to individualize medication selection and dosing using genetic data. However, many practicing pharmacists may feel ill-equipped to interpret pharmacogenomic test results because of insufficient education and training. Evidence-based, updated, and freely available resources such as the Clinical Pharmacogenetics Implementation Consortium guidelines can help pharmacists interpret and apply pharmacogenomic test results to patient care. Although gaps for the application of pharmacogenomic information exist, this commentary aims to demystify the interpretation of pharmacogenomic test results and empower pharmacists to apply genetic data alongside other clinical variables to optimize medication-related outcomes for their patients. An "ABCD" framework is proposed to guide pharmacists through the steps: (1) Actionability - Are the gene(s) clinically relevant for the patient? (2) Be Mindful of Limitations - What are the caveats with pharmacogenomic test results and reports? (3) Clinical Practice Guidelines - How do you use pharmacogenomic test results to guide clinical decision-making? and (4) Document and Discuss - How do you educate the patient about their pharmacogenomic test results and document the results for future use? Key concepts are illustrated using a psychiatric patient case example.

Genetic Screening-Emerging Issues

In many countries, some form of genetic screening is offered to all or part of the population, either in the form of well-organized screening programs or in a less formalized way. Screening can be offered at different phases of life, such as preconception, prenatal, neonatal and later in life. Screening should only be offered if the advantages outweigh the disadvantages. Technical innovations in testing and treatment are driving changes in the field of prenatal and neonatal screening, where many jurisdictions have organized population-based screening programs. As a result, a greater number and wider range of conditions are being added to the programs, which can benefit couples' reproductive autonomy (preconception and prenatal screening) and improve early diagnosis to prevent irreversible health damage in children (neonatal screening) and in adults (cancer and cascade screening). While many developments in screening are technology-driven, citizens may also express a demand for innovation in screening, as was the case with non-invasive prenatal testing. Relatively new emerging issues for genetic screening, especially if testing is performed using DNA sequencing, relate to organization, data storage and interpretation, benefit-harm ratio and distributive justice, information provision and follow-up, all connected to acceptability in current healthcare systems.

Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology

Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.

Mining local exome and HLA data to characterize pharmacogenetic variants in Saudi Arabia

Pharmacogenomics (PGx) is a promising field of precision medicine where efficacy of drugs is maximized while side effects are minimized for individual patients. Knowledge of the frequency of PGx-relevant variants (pharmacovariants) in the local population is a pre-requisite to informed policy making. Unfortunately, such knowledge is largely lacking from the Middle East. Here, we describe the use of a large clinical exome database (n = 13,473) and HLA haplotypes (n = 64,737) from Saudi Arabia, one of the largest countries in the Middle East, along with previously published data from the local population to ascertain allele frequencies of known pharmacovariants. In addition, we queried another exome database (n = 816) of well-phenotyped research subjects from Saudi Arabia to discover novel candidate variants in known PGx genes (pharmacogenes). Although our results show that only 26% (63/242) of class 1A/1B PharmGKB variants were identified, we estimate that 99.57% of the local population have at least one such variant. This translates to a minimum estimated impact of 9% of medications dispensed by our medical center annually. We also highlight the contribution of rare variants where 71% of the pharmacogenes devoid of common pharmacovariants had at least one potentially deleterious rare variant. Thus, we show that approaches that go beyond the use of commercial PGx kits that have been optimized for other populations should be implemented to ensure universal and equitable access of all members of the local population to personalized prescription practices.

Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes

Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targets such as drug-metabolizing enzymes or transporters to predict differences in the patient's phenotype. However, there is evidence that the phenotype-genotype concordance is limited. Thus, we discuss different phenotyping strategies using exogenous xenobiotics (e.g., drug cocktails) or endogenous compounds for phenotype prediction. In particular, minimally invasive approaches focusing on liquid biopsies offer great potential to preemptively determine metabolic and transport capacities. Early studies indicate that ADME phenotyping using exosomes released from the liver is reliable. In addition, pharmacometric modeling and artificial intelligence improve phenotype prediction. However, further prospective studies are needed to demonstrate the clinical utility of individualized treatment based on phenotyping strategies, not only relying on genetics. The present review summarizes current knowledge and limitations.

SLCO1B1 functional variants and statin-induced myopathy in people with recent genealogical ancestors from Africa: a population-based real-world study

Background

Clinical pharmacogenetic implementation guidelines for statin therapy are derived from evidence of primarily Eurocentric study populations. Functional SLCO1B1 variants that are rare in these study populations have not been investigated as a determinant of statin myotoxicity and are thus missing from guideline inclusion.

Objective

Determine the relationship between candidate functional SLCO1B1 variants and statin-induced myopathy in people with recent genealogical ancestors from Africa.

Design

Population-based pharmacogenetic study using real-world evidence from electronic health record-linked biobanks.

Setting

Various health care settings.

Participants

Self-identified white and Black statin users with genome-wide genotyping data available.

Measurements

Primarily, the odds of statin-induced myopathy + rhabdomyolysis. Secondarily, total bilirubin levels. Thirdly, cell-based functional assay results.

Results

Meta-analyses results demonstrated an increased risk of statin-induced myopathy + rhabdomyolysis with c.481+1G>T (odds ratio [OR] = 3.27, 95% confidence interval [CI] 1.43-7.46, P =.005) and c.1463G>C (OR = 2.45, 95% CI 1.04-5.78, P =.04) for Black participants. For White participants, c.521T>C was also significantly associated with increased risk of statin-induced myopathy + rhabdomyolysis (OR = 1.41, 95% CI 1.20-1.67, P =5.4x10 -5 ). This effect size for c.521T>C was similar in the Black participants, but did not meet the level of statistical significance (OR = 1.47, 95% CI 0.58-3.73, P =0.41). Supporting evidence using total bilirubin as an endogenous biomarker of SLCO1B1 function as well as from cell-based functional studies corroborated these findings.

Limitations

Data limited to severe statin myotoxicity events.

Conclusion

Our findings implicate Afrocentric SLCO1B1 variants on preemptive pharmacogenetic testing panels, which could have an instant impact on reducing the risk of statin-associated myotoxicity in historically excluded groups.

Primary Funding Source

National Institutes of Health, Office of the Director - All of Us (OD-AoURP).

Influencia de la farmacogenética en la diversidad de respuesta a las estatinas asociada a las reacciones adversas

Introducción

Las estatinas son unos de los medicamentos más prescritos en los países desarrollados por ser el tratamiento de elección para reducir los niveles de colesterol ayudando así a prevenir la enfermedad cardiovascular. Sin embargo, un gran número de pacientes sufre reacciones adversas, en especial miotoxicidad. Entre los factores que influyen en la diversidad de respuesta, la farmacogenética puede jugar un papel relevante especialmente en la prevención de los efectos adversos asociados a estos medicamentos.

Contenido

Revisión de los conocimientos actuales sobre la influencia de la farmacogenética en la aparición y prevención de las reacciones adversas asociadas a estatinas, así como del beneficio clínico del test farmacogenético anticipado.

Resumen

Variaciones genéticas en SLCO1B1 (rs4149056) para todas las estatinas; en ABCG2 (rs2231142) para rosuvastatina; o en CYP2C9 (rs1799853 y rs1057910) para fluvastatina están asociadas a un incremento de las reacciones adversas de tipo muscular y a una baja adherencia al tratamiento. Además, diversos fármacos inhibidores de estos transportadores y enzimas de biotransformación incrementan la exposición sistémica de las estatinas favoreciendo la aparición de las reacciones adversas.

Perspectiva

La implementación clínica del análisis anticipado de este panel de farmacogenética evitaría en gran parte la aparición de reacciones adversas. Además, la estandarización en la identificación de los efectos adversos, en la metodología e interpretación del genotipo, permitirá obtener resultados más concluyentes sobre la asociación entre las variantes genéticas del SLCO1B1, ABCG y CYP2C9 y la aparición de reacciones adversas y establecer recomendaciones para alcanzar tratamientos más personalizados para cada estatina.

Influence of pharmacogenetics on the diversity of response to statins associated with adverse drug reactions

Background

Statins are one of the most prescribed medications in developed countries as the treatment of choice for reducing cholesterol and preventing cardiovascular diseases. However, a large proportion of patients experience adverse drug reactions, especially myotoxicity. Among the factors that influence the diversity of response, pharmacogenetics emerges as a relevant factor of influence in inter-individual differences in response to statins and can be useful in the prevention of adverse drug effects.

Content

A systematic review was performed of current knowledge of the influence of pharmacogenetics on the occurrence and prevention of statin-associated adverse reactions and clinical benefits of preemptive pharmacogenetics testing.

Summary

Genetic variants SLCO1B1 (rs4149056) for all statins; ABCG2 (rs2231142) for rosuvastatin; or CYP2C9 (rs1799853 and rs1057910) for fluvastatin are associated with an increase in muscle-related adverse effects and poor treatment adherence. Besides, various inhibitors of these transporters and biotransformation enzymes increase the systemic exposure of statins, thereby favoring the occurrence of adverse drug reactions.

Outlook

The clinical preemptive testing of this pharmacogenetic panel would largely prevent the incidence of adverse drug reactions. Standardized methods should be used for the identification of adverse effects and the performance and interpretation of genotyping test results. Standardization would allow to obtain more conclusive results about the association between SLCO1B1, ABCG and CYP2C9 variants and the occurrence of adverse drug reactions. As a result, more personalized recommendations could be established for each statin.

Evolution of pharmacogenomic services and implementation of a multi-state pharmacogenomics clinic across a large rural healthcare system

Introduction: Pharmacogenomics (PGx) aims to maximize drug benefits while minimizing risk of toxicity. Although PGx has proven beneficial in many settings, clinical uptake lags. Lack of clinician confidence and limited availability of PGx testing can deter patients from completing PGx testing. A few novel PGx clinic models have been described as a way to incorporate PGx testing into the standard of care. Background: A PGx clinic was implemented to fill an identified gap in provider availability, confidence, and utilization of PGx across our health system. Through a joint pharmacist and Advanced Practice Provider (APP) collaborative clinic, patients received counseling and PGx medication recommendations both before and after PGx testing. The clinic serves patients both in-person and virtually across four states in the upper Midwest. Results: The majority of patients seen in the PGx clinic during the early months were clinician referred (77%, n = 102) with the remainder being self-referred. Patients were, on average, taking two medications with Clinical Pharmacogenetics Implementation Consortium guidelines. Visits were split almost equally between in-person and virtual visits. Conclusion: Herein, we describe the successful implementation of an interdisciplinary PGx clinic to further enhance our PGx program. Throughout the implementation of the PGx clinic we have learned valuable lessons that may be of interest to other implementors. Clinicians were actively engaged in clinic referrals and early adoption of telemedicine was key to the clinic's early successes.

Intersection and Considerations for Patient-Centered Care, Patient Experience, and Medication Experience in Pharmacogenomics

As healthcare continues to embrace the concept of person- and patient-centered care, pharmacogenomics, patient experience, and medication experience will continue to play an increasingly important role in care delivery. This review highlights the intersection between these concepts and provides considerations for patient-centered medication and pharmacogenomic experiences. Elements at the patient, provider, and system level can be considered in the discussion, supporting the use of pharmacogenomics, with components of the patient and medication experience contributing to the mitigation of barriers surrounding patient use and the valuation of pharmacogenomic testing.

Lessons from clinical implementation of a preemptive pharmacogenetic panel as part of a testing pilot program with an employer-sponsored medical plan

Introduction: This manuscript reports on a pilot program focused on implementing pharmacogenetic testing within the framework of an employer-sponsored medical plan at University of Florida (UF) Health. The aim was to understand the challenges associated with program implementation and to gather insights into patient attitudes towards PGx testing. Methods: The pilot program adopted a partially preemptive approach, targeting patients on current prescriptions for medications with relevant gene-drug associations. Patients were contacted via phone or through the MyChart system and offered pharmacogenetic testing with no additional direct costs. Results: Of 244 eligible patients, 110 agreed to participate. However, only 61 returned the mailed DNA collection kits. Among these, 89% had at least one potentially actionable genotype-based phenotype. Post-test follow-up revealed that while the majority viewed the process positively, 71% preferred a consultation with a pharmacogenetic specialist for better understanding of their results. Barriers to implementation ranged from fatigue with the healthcare system to a lack of understanding of the pharmacogenetic testing and concerns about privacy and potential misuse of genetic data. Conclusion: The findings underscore the need for clearer patient education on pharmacogenetic results and suggest the importance of the role of pharmacogenetic-trained pharmacists in delivering this education. They also highlight issues with relying on incomplete or inaccurate medication lists in patients' electronic health record. The implementation revealed less obvious challenges, the understanding of which could be beneficial for the success of future preemptive pharmacogenetic implementation programs. The insights from the pilot program served to bridge the information gap between patients, providers, and pharmacogenetic -specialists, with the ultimate goal of improving patient care.

Clinical Pharmacogenomic MT-RNR1 Screening for Aminoglycoside-Induced Ototoxicity and the Post-Test Counseling Conundrum

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.

Pharmacogenetic Guided Opioid Therapy Improves Chronic Pain Outcomes and Comorbid Mental Health: A Randomized, Double-Blind, Controlled Study

Interindividual variability in analgesic response is at least partly due to well-characterized polymorphisms that are associated with opioid dosing and adverse outcomes. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has put forward recommendations for the CYP2D6 phenotype, but the list of studied drug-gene pairs continues to grow. This clinical trial randomized chronic pain patients (n = 60), referred from primary care to pain unit care into two opioid prescribing arms, one guided by CYP2D6, μ-opioid receptor (OPRM1), and catechol-O-methyl transferase (COMT) genotypes vs. one with clinical routine. The genotype-guided treatment reduced pain intensity (76 vs. 59 mm, p < 0.01) by improving pain relief (28 vs. 48 mm, p < 0.05), increased quality of life (43 vs. 56 mm p < 0.001), and lowered the incidence of clinically relevant adverse events (3 [1-5] vs. 1 [0-2], p < 0.01) and 42% opioid dose (35 [22-61] vs. 60 [40-80] mg/day, p < 0.05) as opposed to usual prescribing arm. The final health utility score was significantly higher (0.71 [0.58-0.82] vs. 0.51 [0.13-0.67] controls, p < 0.05) by improving sleepiness and depression comorbidity, with a significant reduction of 30-34% for headache, dry mouth, nervousness, and constipation. A large-scale implementation analysis could help clinical translation, together with a pharmaco-economic evaluation.

Pharmacogenomics of Hypertension in Africa: Paving the Way for a Pharmacogenetic-Based Approach for the Treatment of Hypertension in Africans

In Africa, the burden of hypertension has been rising at an alarming rate for the last two decades and is a major cause for cardiovascular disease (CVD) mortality and morbidity. Hypertension is characterised by elevated blood pressure (BP) ≥ 140/90 mmHg. Current hypertension guidelines recommend the use of antihypertensives belonging to the following classes: calcium channel blockers (CCB), angiotensin converting inhibitors (ACEI), angiotensin receptor blockers (ARB), diuretics, β-blockers, and mineralocorticoid receptor antagonists (MRAs), to manage hypertension. Still, a considerable number of hypertensives in Africa have their BP uncontrolled due to poor drug response and remain at the risk of CVD events. Genetic factors are a major contributing factor, accounting for 20% to 80% of individual variability in therapy and poor response. Poor response to antihypertensive drug therapy is characterised by elevated BPs and occurrence of adverse drug reactions (ADRs). As a result, there have been numerous studies which have examined the role of genetic variation and its influence on antihypertensive drug response. These studies are predominantly carried out in non-African populations, including Europeans and Asians, with few or no Africans participating. It is important to note that the greatest genetic diversity is observed in African populations as well as the highest prevalence of hypertension. As a result, this warrants a need to focus on how genetic variation affects response to therapeutic interventions used to manage hypertension in African populations. In this paper, we discuss the implications of genetic diversity in CYP11B2, GRK4, NEDD4L, NPPA, SCNN1B, UMOD, CYP411, WNK, CYP3A4/5, ACE, ADBR1/2, GNB3, NOS3, B2, BEST3, SLC25A31, LRRC15 genes, and chromosome 12q loci on hypertension susceptibility and response to antihypertensive therapy. We show that African populations are poorly explored genetically, and for the few characterised genes, they exhibit qualitative and quantitative differences in the profile of pharmacogene variants when compared to other ethnic groups. We conclude by proposing prioritization of pharmacogenetics research in Africa and possible adoption of pharmacogenetic-guided therapies for hypertension in African patients. Finally, we outline the implications, challenges, and opportunities these studies present for populations of non-European descent.

Comparison of targeted vs. expanded pharmacogenomic testing: What are we missing?

BACKGROUND

Pharmacogenomics (PGx) is used as a medication management strategy by a small but growing number of institutions. PGx allows prescribers to individually treat patients concordant with their genes. Recent litigation for preventable PGx-mediated adverse events highlights the need to accelerate PGx implementation for patient safety. Genetic variations cause drug metabolism, transport, and target changes, affecting medication response and tolerability. PGx testing often consists of targeted testing aimed at specific gene-drug pairs or disease states. Conversely, expanded panel testing can evaluate all known actionable gene-drug interactions, enhancing proactive clarity regarding patient response.

OBJECTIVES

Evaluate the divergence of targeted PGx testing with a single gene-drug pair test (cardiac), a two-gene panel, and a focused psychiatric panel compared to expanded PGx testing.

METHODS

An expanded PGx panel (≥25 genes) was compared to a single gene-drug pair test of CYP2C19/clopidogrel, a dual gene test of CYP2C19/CYP2D6, a 7-gene psychiatric list, and a 14-gene psychiatric panel to inform specific depression and pain management drugs. The expanded panel provided a baseline to evaluate total PGx variations compared to those possibly missed by targeted testing.

RESULTS

Targeted testing did not identify up to 95% of total PGx gene-drug interactions discovered. The expanded panel reported all gene-drug interactions for any medication with Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance or U.S. Food and Drug Administration (FDA) labeling for that gene. Single gene CYP2C19/clopidogrel testing missed or did not report on ∼95% of total interactions, CYP2C19/CYP2D6 testing missed or did not report ∼89%, and the 14-gene panel missed or did not report on ∼73%. The 7-gene list missed ∼20% of discovered potential PGx interactions but was not designed to identify gene-drug interactions.

CONCLUSIONS

Targeted PGx testing for limited genes or by specialty may miss or not report significant portions of PGx gene-drug interactions. This can lead to potential patient harm from the missed interactions and subsequent failed therapies and/or adverse reactions.

Pharmacogenetic Testing in a 70-Year-Old Woman with Polypharmacy and Multiple Comorbidities: A Case Report

BACKGROUND Comorbidities and polypharmacy are difficult to manage, as polypharmacy hinders identification and prevention of medication-related problems. Risk for adverse drug events (ADEs) can be minimized through pharmacogenomic (PGx) testing and related therapeutic adjustments. CASE REPORT A 70-year-old woman with comorbidities and medications enrolled in the Program of All-inclusive Care for the Elderly presented with left lower extremity (LLE) pain, generalized weakness, and major depressive disorder. The provider requested a medication safety review, where the clinical pharmacist-recommended PGx testing given the LLE pain and weakness while taking a statin and inconsistent INR readings taking warfarin. The pharmacist recommended switching atorvastatin to pravastatin to minimize the risk for statin-associated ADEs due to CYP3A4 inhibition and switching fluoxetine to citalopram due to uncontrolled depression/anxiety and to mitigate drug-drug interactions with carvedilol to reduce the risk of orthostatic hypotension. Recommendations were accepted and upon follow-up the patient reported minor LLE pain and improved wellbeing on citalopram. Following PGx testing, the patient had decreased function at SLCO1B1 and was an intermediate metabolizer for CYP2C9 and CYP2D6. This case demonstrates how preemptive PGx testing would have identified drug-gene interactions (DGIs) at the time of prescribing and reduced the risk of statin-associated muscular symptoms, highlighting the utility of panel-based PGx testing in older adults at high risk for ADEs and/or therapy failure. CONCLUSIONS Decreased function at SLCO1B1 increases exposure to statins, leading to statin-induced myalgias, as displayed in this case. PGx testing can help identify DGIs, choose optimal therapies in medically complex older adults, and minimize ADE risk.

A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study

BACKGROUND

The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed.

METHODS

We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants.

FINDINGS

Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001).

INTERPRETATION

Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe.

FUNDING

European Union Horizon 2020.

Early Insights From a Pharmacogenomic-Enriched Comprehensive Medication Management Program Implementation in an Adult Employee Population

OBJECTIVES

The aims of the study are to assess adoption of a pharmacogenomic-enriched comprehensive medication management program in a self-insured employer setting and to better understand medication risks that affect employees.

METHODS

Employees were identified to be at high risk of medication mismanagement and were subsequently provided with a program and process to improve their health. DNA testing, a clinical decision support system, and pharmacists were used to identify medication safety and effectiveness issues and to recommend appropriate changes.

RESULTS

A total of 10.6% of the invited employees enrolled in the program. Actionable recommendations were suggested by pharmacists for 85.8% of employees who completed the program, averaging 5.2 recommendations per person.

CONCLUSIONS

Implementation of a PGx + CMM program in a self-insured employer setting is feasible, detects risks in prescription regimens, and offers opportunities to improve medication management and reduce the burden of healthcare expenses.

Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers

Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.