Translating pharmacogenomics into clinical decisions: do not let the perfect be the enemy of the good

Mapping the Pharmacogenetic Landscape in a Ugandan Population: Implications for Personalized Medicine in an Underrepresented Population

Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience widespread polypharmacy. As population-specific genetic studies are crucial to understanding unique genetic profiles and optimizing treatments to reduce medication-related complications in this diverse population, the present study aims to characterize the pharmacogenomics profile of a rural Ugandan population. We analyzed low-pass whole genome sequencing data from 1998 Ugandans to investigate 18 clinically actionable pharmacogenes in this population. We utilized PyPGx to identify star alleles (haplotype patterns) and compared allele frequencies across populations using the Pharmacogenomics Knowledgebase PharmGKB. Clinical interpretations of the identified alleles were conducted following established dosing guidelines. Over 99% of participants displayed actionable phenotypes across the 18 pharmacogenes, averaging 3.5 actionable genotypes per individual. Several variant alleles known to affect drug metabolism (i.e., CYP3A5*1, CYP2B6*9, CYP3A5*6, CYP2D6*17, CYP2D6*29, and TMPT*3C)-which are generally more prevalent in African individuals-were notably enriched in the Ugandan cohort, beyond reported frequencies in other African peoples. More than half of the cohort exhibited a predicted impaired drug response associated with CFTR, IFNL3, CYP2B6, and CYP2C19, and approximately 31% predicted altered CYP2D6 metabolism. Potentially impaired CYP2C9, SLCO1B1, TPMT, and DPYD metabolic phenotypes were also enriched in Ugandans compared with other African populations. Ugandans exhibit distinct allele profiles that could impact drug efficacy and safety. Our findings have important implications for pharmacogenomics in Uganda, particularly with respect to the treatment of prevalent communicable and non-communicable diseases, and they emphasize the potential of pharmacogenomics-guided therapies to optimize healthcare outcomes and precision medicine in Uganda.

Utilizing Pharmacogenomics Results to Guide Antidepressant Selection: A Case Report

The case discussion demonstrates the benefit of using Pharmacogenomic (PGx) results to aid in the selection of antidepressant therapy and improve response to treatment. Nearly half of patients diagnosed with major depressive disorder fail initial therapy and may require multiple trials of antidepressants. Genetic variation in several metabolic enzymes contribute to the variable response to antidepressant therapy. PGx testing provides an opportunity to inform antidepressant selection and optimize therapeutic outcomes, while minimizing risk of adverse events. A 79-year-old female who had been experiencing a suboptimal response to escitalopram following dose escalation over a period of three years was referred for a PGx consultation. A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions, and relevant clinical information to recommend alternative antidepressant therapy, which resulted in mood improvement.

Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives

Pharmacogenomics (PGx) is an important component of precision medicine that promises tailored treatment approaches based on an individual's genetic information. Exploring the initiatives in research that help to integrate PGx test into clinical setting, identifying the potential barriers and challenges as well as planning the future directions, are all important for fruitful PGx implementation in any population. Qatar serves as an exemplar case study for the Middle East, having a small native population compared to a diverse immigrant population, advanced healthcare system, national genome program, and several educational initiatives on PGx and precision medicine. This paper attempts to outline the current state of PGx research and implementation in Qatar within the global context, emphasizing ongoing initiatives and educational efforts. The inclusion of PGx in university curricula and healthcare provider training, alongside precision medicine conferences, showcase Qatar's commitment to advancing this field. However, challenges persist, including the requirement for population specific implementation strategies, complex genetic data interpretation, lack of standardization, and limited awareness. The review suggests policy development for future directions in continued research investment, conducting clinical trials for the feasibility of PGx implementation, ethical considerations, technological advancements, and global collaborations to overcome these barriers.

Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

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.

Assessing Clinical Utility of Pharmacogenetic Testing in the Military Health System

INTRODUCTION

Response to medications can differ widely among individual patients. Adverse drug reactions can lead to serious morbidity and mortality. Pharmacogenetic (PGx) testing can predict responses to medications and increased risks of adverse events where the genetic basis is understood. Several published manuscripts suggest positive impacts of systematic preemptive PGx testing. However, few studies have been conducted on PGx implementation in the Military Health System (MHS).

MATERIAL AND METHODS

A cross-sectional study of adult beneficiaries in a primary care clinic at a large military treatment facility was conducted in 2022. Participants underwent PGx genotyping of CYP2C19 and CYP2D6 genes at the Defense Health Agency Genetics Reference Laboratory. Participant medication lists were compared to the current Clinical Pharmacogenetic Implementation Consortium (CPIC) PGx gene-drug guidelines to assess potential actionability of these results.

RESULTS

Genotyping of CYP2C19 and CYP2D6 in 165 MHS beneficiaries (mean age: 65 years) revealed that 81.2% of participants had at least one abnormal PGx finding. Among those with an abnormal PGx result, 65% were taking a medication listed on the CPIC website with an association with the particular gene in which the finding was identified. In addition, 78% of all of the participants in the study were taking at least one medication that is metabolized by CYP2C19 or CYP2D6 with associated CPIC guidelines.

CONCLUSIONS

Pharmacogenetic testing for CYP2C19 and CYP2D6 identified a substantial proportion of MHS patients at a single center who could benefit from evaluation of current medication regimens based on the CPIC guidelines. Individualized medical management may be warranted to a greater degree than previously recognized based on the findings given possible differences in medication metabolism. Many MHS beneficiaries already take medications metabolized by CYP2C19 and CYP2D6, and a substantial proportion may be at risk for preventable adverse events for medications metabolized by these enzymes. While preliminary, a large number of actionable polymorphisms among a relatively small set of individuals taking at-risk medications suggest that implementing PGx testing in clinical practice may be beneficial in the MHS with appropriate clinical infrastructure.

Moving towards the implementation of pharmacogenetic testing in Quebec

Clinical implementation of pharmacogenetics (PGx) into routine care will elevate the current paradigm of treatment decisions. However, while PGx tests are increasingly becoming reliable and affordable, several barriers have limited their widespread usage in Canada. Globally, over ninety successful PGx implementors can serve as models. The purpose of this paper is to outline the PGx implementation barriers documented in Quebec (Canada) to suggest efficient solutions based on existing PGx clinics and propose an adapted clinical implementation model. We conclude that the province of Quebec is ready to implement PGx.

Feasibility of preemptive pharmacogenetic testing and improvement of medication treatment satisfaction among medically underserved patients

Previous findings suggest that medically underserved patients are prescribed medications with pharmacogenetic (PGx) guidelines at a high frequency. Thus, underserved patients may especially benefit from PGx testing, but little evidence exists regarding the effect of testing in this population. This pilot study aimed to generate key feasibility data and explore clinical outcomes of PGx implementation in underserved populations. Black and Latino patients were recruited from an outpatient clinic and underwent PGx testing. Feasibility measures included enrollment metrics and actionable genotype frequencies. The primary clinical outcome was patient medication treatment satisfaction 6 months after testing. Implementation outcomes included the number of healthcare provider encounters and medication changes within the 6-month follow-up. Effectiveness outcomes included medication adherence, patient-perceived test value, and time spent discussing medications with providers. Ninety-nine patients completed the study. Proton-pump inhibitors were the most frequent PGx drug class prescribed at baseline (61%) followed by nonsteroidal anti-inflammatory drugs (36%). Patients with an actionable genotype constituted 96% of the population, whereas 28% had an actionable genotype related to their PGx drug. Patient treatment satisfaction significantly increased over the 6 months after PGx testing. In addition, medication adherence and the number of provider encounters significantly increased over the study period. In a pilot study, preemptive PGx testing was feasible in primary care clinics, improved patient treatment satisfaction and adherence, and increased the number of provider encounters in medically underserved patients. Future clinical trials are warranted to assess the long-term effects of PGx testing in a larger diverse patient population.

Clinical utilities and end-user experience of pharmacogenomics: 39 mo of clinical implementation experience in an Australian hospital setting

BACKGROUND

Pharmacogenomics (PG) testing is under-utilised in Australia. Our research provides Australia-specific data on the perspectives of patients who have had PG testing and those of the clinicians involved in their care, with the aim to inform wider adoption of PG into routine clinical practice.

AIM

To investigate the frequency of actionable drug gene interactions and assess the perceived utility of PG among patients and clinicians.

METHODS

We conducted a retrospective audit of PG undertaken by 100 patients at an Australian public hospital genetics service from 2018 to 2021. Via electronic surveys we compared and contrasted the experience, understanding and usage of results between these patients and their clinicians.

RESULTS

Of 100 patients who had PG, 84% were taking prescription medications, of which 67% were taking medications with actionable drug-gene interactions. Twenty-five out of 81 invited patients and 17 out of 89 invited clinicians completed the surveys. Sixty-eight percent of patients understood their PG results and 48% had medications changed following testing. Paired patient-clinician surveys showed patient-perceived utility and experience was positive, contrasting their clinicians’ hesitancy on PG adoption who identified insufficient education/training, lack of clinical support, test turnaround time and cost as barriers to adoption.

CONCLUSION

Our dichotomous findings between the perspectives of our patient and clinician cohorts suggest the uptake of PG is likely to be driven by patients and clinicians need to be prepared to provide information and guidance to their patients.

Ethnopsychopharmacology: Clinical and scientific writing pearls

The concept of ethnopsychopharmacology aims to predict or explain the pharmacologic response to psychiatric medications based on the influence of biologic and nonbiologic factors. Interactions involving these factors are complex and influence patient outcomes in health care. Pharmacists and other clinicians working in patient care environments, research, or medical education should engage in lifelong learning to enhance ethnopsychopharmacologic knowledge gaps, which ultimately may improve and individualize care across diverse populations. Through two cases, this paper provides pearls on how biogeographical ancestry and cytochrome P450 status may influence pharmacotherapy selection, dosing, or response. A third scenario highlights a publication, like many other published works, with deficiencies in how data on ancestry, race, and ethnicity are collected or reported. Current recommendations on the use of inclusive language in scientific writing are reviewed, with attention to specific examples.

Towards more accurate pharmacogenomic variant effect predictions

Tweetable abstract Accurate variant interpretation has become a key bottleneck for the translation of an individual's pharmacogenome into actionable recommendations. We recommend an integrated use of multiplexed assays, structure-based predictions and biobank data to develop more accurate effect predictors.

Pharmacogenomics implementation across multiple clinic settings: a qualitative evaluation

Aim: To advance clinical adoption and implementation of pharmacogenomics (PGx) testing, barriers and facilitators to these efforts must be understood. This study identified and examined barriers and facilitators to active implementation of a PGx program across multiple clinic settings in an academic healthcare system. Materials & methods: 28 contributors to the PGx implementation (e.g., clinical providers, informatics specialists) completed an interview to elicit their perceptions of the implementation. Results: Qualitative analysis identified several barriers and facilitators that spanned different stages of the implementation process. Specifically, unclear test payment mechanisms, decision support tool development, rigid workflows and provider education were noted as barriers to the PGx implementation. A multidisciplinary implementation team and leadership support emerged as key facilitators. Furthermore, participants also suggested strategies to overcome or maintain these factors. Conclusion: Assessing real-world implementation perceptions and suggested strategies from a range of implementation contributors facilitates a more comprehensive framework and best-practice guidelines for PGx implementation.

Reassessing pharmacogenomic cell sensitivity with multilevel statistical models

Pharmacogenomic experiments allow for the systematic testing of drugs, at varying dosage concentrations, to study how genomic markers correlate with cell sensitivity to treatment. The first step in the analysis is to quantify the response of cell lines to variable dosage concentrations of the drugs being tested. The signal to noise in these measurements can be low due to biological and experimental variability. However, the increasing availability of pharmacogenomic studies provides replicated data sets that can be leveraged to gain power. To do this, we formulate a hierarchical mixture model to estimate the drug-specific mixture distributions for estimating cell sensitivity and for assessing drug effect type as either broad or targeted effect. We use this formulation to propose a unified approach that can yield posterior probability of a cell being susceptible to a drug conditional on being a targeted effect or relative effect sizes conditioned on the cell being broad. We demonstrate the usefulness of our approach via case studies. First, we assess pairwise agreements for cell lines/drugs within the intersection of two data sets and confirm the moderate pairwise agreement between many publicly available pharmacogenomic data sets. We then present an analysis that identifies sensitivity to the drug crizotinib for cells harboring EML4-ALK or NPM1-ALK gene fusions, as well as significantly down-regulated cell-matrix pathways associated with crizotinib sensitivity.

Incorporating Omics and Precision Health in a Nursing PhD Program: The Perspectives of Student Nurse Scientists

ABSTRACT

To engage in innovative and novel precision health and omics research, nurse scientists need to be knowledgeable about the genetic, behavioral, and environmental factors that impact health outcomes. This article illustrates the benefits of a nursing omics PhD curriculum at a state university. The purpose is to provide students' perspectives and research interests that were inspired by the omics and precision health curriculum. Exposing these early-career PhD nursing student scientists to omics and precision health engaged them to think broadly about the potential to generate original nurse-led research.

Pharmacogenomic panel testing provides insight and enhances medication management in people with HIV

OBJECTIVE

Our study aimed to assess the impact of pharmacogenomic panel testing in people with HIV (PWH).

DESIGN

Prospective, observational intervention assessment.

METHODS

One hundred PWH were provided a comprehensive pharmacogenomic panel during routine care visits within the HIV specialty clinic of a large academic medical center. The panel determined the presence of specific genetic variants that could predict response or toxicity to commonly prescribed antiretroviral therapy (ART) and non-ART medications. An HIV specialty pharmacist reviewed the results with participants and the care team. The pharmacist (1) recommended clinically actionable interventions based on the participants' current drug therapy, (2) assessed for genetic explanations for prior medication failures, adverse effects, or intolerances, and (3) advised on potential future clinically actionable care interventions based on individual genetic phenotypes.

RESULTS

Ninety-six participants (median age 53 years, 74% white, 84% men, 89% viral load <50 copies/ml) completed panel testing, yielding 682 clinically relevant pharmacogenomic results (133 major, 549 mild-moderate). Ninety participants (89 on ART) completed follow-up visits with 65 (72%) receiving clinical recommendations based on current medication profiles. Of the 105 clinical recommendations, 70% advised additional monitoring for efficacy or toxicity, and 10% advised alteration of drug therapy. Panel results offered explanation for prior ART inefficacy in one participant and ART intolerance in 29%. Genetic explanation for non-ART toxicity was seen in 21% of participants, with genetic contributors to inefficacy of non-ART therapy identified in 39% of participants.

CONCLUSION

Preliminary data in a small cohort of PWH demonstrates benefit of routine pharmacogenomic panel testing.

Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics

BACKGROUND

This pilot study aims to identify and functionally assess pharmacovariants in whole exome sequencing data. While detection of known variants has benefited from pharmacogenomic-dedicated bioinformatics tools before, in this paper we have tested novel deep computational analysis in addition to artificial intelligence as possible approaches for functional analysis of unknown markers within less studied drug-related genes.

METHODS

Pharmacovariants from 1800 drug-related genes from 100 WES data files underwent (a) deep computational analysis by eight bioinformatic algorithms (overall containing 23 tools) and (b) random forest (RF) classifier as the machine learning (ML) approach separately. ML model efficiency was calculated by internal and external cross-validation during recursive feature elimination. Protein modelling was also performed for predicted highly damaging variants with lower frequencies. Genotype-phenotype correlations were implemented for top selected variants in terms of highest possibility of being damaging.

RESULTS

Five deleterious pharmacovariants in the RYR1, POLG, ANXA11, CCNH, and CDH23 genes identified in step (a) and subsequent analysis displayed high impact on drug-related phenotypes. Also, the utilization of recursive feature elimination achieved a subset of 175 malfunction pharmacovariants in 135 drug-related genes that were used by the RF model with fivefold internal cross-validation, resulting in an area under the curve of 0.9736842 with an average accuracy of 0.9818 (95% CI: 0.89, 0.99) on predicting whether a carrying individuals will develop adverse drug reactions or not. However, the external cross-validation of the same model indicated a possible false positive result when dealing with a low number of observations, as only 60 important variants in 49 genes were displayed, giving an AUC of 0.5384848 with an average accuracy of 0.9512 (95% CI: 0.83, 0.99).

CONCLUSION

While there are some technologies for functionally assess not-interpreted pharmacovariants, there is still an essential need for the development of tools, methods, and algorithms which are able to provide a functional prediction for every single pharmacovariant in both large-scale datasets and small cohorts. Our approaches may bring new insights for choosing the right computational assessment algorithms out of high throughput DNA sequencing data from small cohorts to be used for personalized drug therapy implementation.

Current published evidence on barriers and proposed strategies for genetic testing implementation in health care settings: A scoping review

BACKGROUND

The slow uptake of genetic testing in routine clinical practice warrants the attention of researchers and practitioners to find effective strategies to facilitate implementation.

OBJECTIVES

This study aimed to identify the barriers to and strategies for pharmacogenetic testing implementation in a health care setting from published literature.

METHODS

A scoping review was conducted in August 2021 with an expanded literature search using Ovid MEDLINE, Web of Science, International Pharmaceutical Abstract, and Google Scholar to identify studies reporting implementation of pharmacogenetic testing in a health care setting, from a health care system's perspective. Articles were screened using DistillerSR and findings were organized using the 5 major domains of Consolidated Framework for Implementation Research (CFIR).

RESULTS

A total of 3536 unique articles were retrieved from the above sources, with only 253 articles retained after title and abstract screening. Upon screening the full texts, 57 articles (representing 46 unique practice sites) were found matching the inclusion criteria. We found that most reported barriers and their associated strategies to the implementation of pharmacogenetic testing surrounded 2 CFIR domains: intervention characteristics and inner settings. Factors relating to cost and reimbursement were described as major barriers in the intervention characteristics. In the same domain, another major barrier was the lack of utility studies to provide evidence for genetic testing uptake. Technical hurdles, such as integrating genetic information to medical records, were identified as an inner settings barrier. Collaborations and lessons from early implementers could be useful strategies to overcome majority of the barriers across different health care settings. Strategies proposed by the included implementation studies to overcome these barriers are summarized and can be used as guidance in future.

CONCLUSION

Barriers and strategies identified in this scoping review can provide implementation guidance for practice sites that are interested in implementing genetic testing.

Prescription medications with actionable pharmacogenomic recommendations in Veterans Health Administration patients

Aim: To evaluate the prevalence of medications with actionable pharmacogenomic (PGx) safety and efficacy recommendations in patients receiving care from the Veterans Health Administration. Materials & methods: Outpatient prescription data from 2011 to 2021 and any documented adverse drug reactions (ADRs) were reviewed for those who received PGx testing at one Veterans Administration location between November 2019 and October 2021. Results: Among the reviewed prescriptions, 381 (32.8%) were associated with an actionable recommendation based on the Clinical Pharmacogenetics Implementation Consortium (CPIC) prescribing guidelines, with 205 (17.7%) for efficacy concerns and 176 (15.2%) for safety concerns. Among those with a documented ADR for a PGx-impacted medication, 39.1% had PGx results that aligned with CPIC recommendations. Conclusion: Medications with actionable PGx recommendations for safety and efficacy concerns are received with similar frequency, and most patients who have undergone PGx testing at the Phoenix Veterans Administration have received medications that may be impacted by PGx testing.

Pharmacogenomics in practice: a review and implementation guide

Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests' reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.

An Integrated Multidisciplinary Circuit Led by Hospital and Community Pharmacists to Implement Clopidogrel Pharmacogenetics in Clinical Practice

The use of pharmacogenetics to optimize pharmacotherapy is growing rapidly. This study evaluates the feasibility and operability of a collaborative circuit involving hospital and community pharmacists to implement clopidogrel pharmacogenetics in Barcelona, Catalonia, Spain. We aimed to enroll patients with a clopidogrel prescription from cardiologists at the collaborating hospital. Community pharmacists collected patients' pharmacotherapeutic profiles and saliva samples, which were then sent to the hospital for CYP2C19 genotyping. Hospital pharmacists collated the obtained data with patients' clinical records. Data were analyzed jointly with a cardiologist to assess the suitability of clopidogrel. The provincial pharmacists' association coordinated the project and provided IT and logistic support. The study began in January 2020. However, it was suspended in March 2020 due to the COVID-19 pandemic. At that moment, 120 patients had been assessed, 16 of whom met the inclusion criteria and were enrolled in the study. The processing of samples obtained before the pandemic had an average delay of 13.8 ± 5.4 days. A total of 37.5% patients were intermediate metabolizers and 18.8% were ultrarapid metabolizers. No poor metabolizers were detected. Pharmacists rated their experience with a 7.3 ± 2.7 likelihood of recommending that fellow pharmacists participate. The net promoter score among participating pharmacists was +10%. Our results show that the circuit is feasible and operable for further initiatives.

Pharmacogenomics in Stroke and Cardiovascular Disease: State of the Art

There is considerable interindividual variability in the response to antiplatelet and anticoagulant therapies, and this variation may be attributable to genetic variants. There has been an increased understanding of the genetic architecture of stroke and cardiovascular disease, which has been driven by advancements in genomic technologies and this has raised the possibility of more targeted pharmaceutical treatments. Pharmacogenetics promises to use a patient's genetic profile to treat those who are more likely to benefit from a particular intervention by selecting the best possible therapy. Although there are numerous studies indicating strong evidence for the effect of specific genotypes on the outcomes of vascular drugs, the adoption of pharmacogenetic testing in clinical practice has been slow. This resistance may stem from sometimes conflicting findings among pharmacogenetic studies, a lack of stroke-specific randomized controlled trials to test the effectiveness of genetically-guided therapies, and the practical and cost-effective implementation of genetic testing within the clinic. Thus, this review provides an overview of the genetic variants that influence the individual responses to aspirin, clopidogrel, warfarin and statins and the different methods for pharmacogenetic testing and guidelines for clinical implementation for stroke patients.

Starring Role of Biomarkers and Anticancer Agents as a Major Driver in Precision Medicine of Cancer Therapy

Precision medicine is the most modern contemporary medicine approach today, based on great amount of data on people's health, individual characteristics, and life circumstances, and employs the most effective ways to prevent and cure diseases. Precision medicine in cancer is the most precise and viable treatment for every cancer patient based on the disease's genetic profile. Precision medicine changes the standard one size fits all medication model, which focuses on average responses to care. Consolidating modern methodologies for streamlining and checking anticancer drugs can have long-term effects on understanding the results. Precision medicine can help explicit anticancer treatments using various drugs and even in discovery, thus becoming the paradigm of future cancer medicine. Cancer biomarkers are significant in precision medicine, and findings of different biomarkers make this field more promising and challenging. Naturally, genetic instability and the collection of extra changes in malignant growth cells are ways cancer cells adapt and survive in a hostile environment, for example, one made by these treatment modalities. Precision medicine centers on recognizing the best treatment for individual patients, dependent on their malignant growth and genetic characterization. This new era of genomics progressively referred to as precision medicine, has ignited a new episode in the relationship between genomics and anticancer drug development.

Identifying the prevalence of clinically actionable drug-gene interactions in a health system biorepository to guide pharmacogenetics implementation services

Understanding patterns of drug-gene interactions (DGIs) is important for advancing the clinical implementation of pharmacogenetics (PGx) into routine practice. Prior studies have estimated the prevalence of DGIs, but few have confirmed DGIs in patients with known genotypes and prescriptions, nor have they evaluated clinician characteristics associated with DGI-prescribing. This retrospective chart review assessed prevalence of DGI, defined as a medication prescription in a patient with a PGx phenotype that has a clinical practice guideline recommendation to adjust therapy or monitor drug response, for patients enrolled in a research genetic biorepository linked to electronic health records (EHRs). The prevalence of prescriptions for medications with pharmacogenetic (PGx) guidelines, proportion of prescriptions with DGI, location of DGI prescription, and clinical service of the prescriber were evaluated descriptively. Seventy-five percent (57,058/75,337) of patients had a prescription for a medication with a PGx guideline. Up to 60% (n = 26,067/43,647) of patients had at least one DGI when considering recommendations to adjust or monitor therapy based on genotype. The majority (61%) of DGIs occurred in outpatient prescriptions. Proton pump inhibitors were the most common DGI medication for 11 of 12 clinical services. Almost 25% of patients (n = 10,706/43,647) had more than one unique DGI, and, among this group of patients, 61% had a DGI with more than one gene. These findings can inform future clinical implementation by identifying key stakeholders for initial DGI prescriptions, helping to inform workflows. The high prevalence of multigene interactions identified also support the use of panel PGx testing as an implementation strategy.

Patients' Perspectives of Factors That Influence Pharmacogenetic Testing Uptake: Enhancing Patient Counseling and Results Dissemination

Patient preferences for pharmacogenetic (PGx) counseling, testing and results dissemination are not well-established, especially in medically underserved Black and Latino populations. The aim of this study was to capture the preferences of Black and Latino patients who received PGx testing to ascertain: (1) factors enhancing their willingness to do testing and (2) preferences for the dissemination of results. Using the constant comparative method, we thematically analyzed interviews with 13 patients from medically underserved populations who had undergone PGx testing. The findings describe participants wanting better medication options, receiving a clear explanation about the testing, valuing or having an interest in science or medicine and having misconceptions about testing results as factors affecting one's willingness to undergo PGx testing. Additionally, patients confirmed preferring receiving results of PGx testing in a sharable format and described the significance of discussing results in a clinical appointment. The findings provide insight into what Black and Latino patients may prefer in terms of clinical implementation of PGx testing. These results can be utilized for tailoring future implementation of PGx testing and informing best pre- and post-test patient counseling and education practices.

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.

Public perceptions of pharmacogenomic services in Ireland - Are people with chronic disease more likely to want service availability than those without? A questionnaire study

Background

As pharmacogenomic services begin to emerge in primary care, the insight of the public is crucial for its integration into clinical practice.

Objectives

To establish perceptions of pharmacogenomics (awareness, understanding, openness to availability, perceived benefits and concerns, willingness to pay, and service setting) and investigate if they differ between those with and without chronic disease(s).

Methods

An anonymous, online questionnaire generated using Qualtrics® and circulated via social media and posters placed in eight participating community pharmacies was conducted with Irish adults. The questions were designed to consider existing literature on patient perceptions of pharmacogenomics. Descriptive statistics were used to summarize questionnaire responses. Chi-square test was used to compare categorical variables, while independent sample t-test and one-way ANOVA were used to compare the mean values of two (with and without chronic disease) and three groups (multimorbidity (two or more chronic conditions) and polypharmacy (prescribed four or more regular medicines) (MMPP), a single chronic disease, and those without existing medical conditions) respectively Logistic regression was used to evaluate age and gender adjusted associations of chronic disease(s) with responses. A p-value <0.05 was considered statistically significant.

Results

A total of 421 responses were received, 30% (n = 120) of whom reported having a chronic disease. Overall, respondents reported low awareness (44%, n = 166) and poor knowledge (55%, n = 212) of pharmacogenomics. After explaining pharmacogenomics to respondents, patients with chronic disease(s) were 2.17 times more likely (p < 0.001) to want pharmacogenomic services availability than those without existing conditions, adjusted for age and gender (driven by preferences of those with MMPP than those with single chronic disease). Respondents demonstrated a high level of interest and noted both the potential benefits and downsides of pharmacogenomic testing. Willingness-to-pay was not associated with having a chronic disease and respondents were more positive about primary care (community pharmacy or general practice) rather than hospital-based pharmacogenomics implementation.

Conclusion

The Irish public in general and those with chronic disease in particular are strongly supportive of pharmacogenomic testing, highlighting an unmet need for its incorporation in medicines optimization. These data underline the need for more research on the implementation of community-based pharmacogenomics services for MMPP patients and ubiquitous pharmacogenomics education programs.

How Dissemination and Implementation Science Can Contribute to the Advancement of Learning Health Systems

Many health systems are working to become learning health systems (LHSs), which aim to improve the value of health care by rapidly, continuously generating evidence to apply to practice. However, challenges remain to advance toward the aspirational goal of becoming a fully mature LHS. While some important challenges have been well described (i.e., building system-level supporting infrastructure and the accessibility of inclusive, integrated, and actionable data), other key challenges are underrecognized, including balancing evaluation rapidity with rigor, applying principles of health equity and classic ethics, focusing on external validity and reproducibility (generalizability), and designing for sustainability. Many LHSs focus on continuous learning cycles, but with limited consideration of issues related to the rapidity of these learning cycles, as well as the sustainability or generalizability of solutions. Some types of data have been consistently underrepresented, including patient-reported outcomes and preferences, social determinants, and behavioral and environmental data, the absence of which can exacerbate health disparities. A promising approach to addressing many challenges that LHSs face may be found in dissemination and implementation (D&I) science. With an emphasis on multilevel dynamic contextual factors, representation of implementation partner engagement, pragmatic research, sustainability, and generalizability, D&I science methods can assist in overcoming many of the challenges facing LHSs. In this article, the authors describe the current state of LHSs and challenges to becoming a mature LHS, propose solutions to current challenges, focusing on the contributions of D&I science with other methods, and propose key components and characteristics of a mature LHS model that others can use to plan and develop their LHSs.

The Apportionment of Pharmacogenomic Variation: Race, Ethnicity, and Adverse Drug Reactions

Fifty years ago, Richard Lewontin found that the vast majority of human genetic variation falls within (~85%) rather than between (~15%) racial groups. This result has been replicated numerous times since and is widely taken to support the notion that genetic differences between racial groups are trivial and thus irrelevant for clinical decision-making. The aim of this study was to consider how the apportionment of pharmacogenomic variation within and between racial and ethnic groups relates to risk disparities for adverse drug reactions. We confirmed that the majority of pharmacogenomic variation falls within (97.3%) rather than between (2.78%) the three largest racial and ethnic groups in the United States: Black, Hispanic, and White. Nevertheless, pharmacogenomic variants showing far greater within than between-group variation can have high predictive value for adverse drug reactions, particularly for minority racial and ethnic groups. We predicted excess adverse drug reactions for minority Black and Hispanic groups, compared to the majority White group, and considered these results in light of the apportionment of genetic variation within and between groups. For 85% within and 15% between group variation, there are 700 excess adverse drug reactions per 1,000 patients predicted for a recessive effect model and 300 for a dominant model. We found high numbers of predicted Black and Hispanic excess adverse drug reactions for widely prescribed platinum chemotherapy compounds, such as cisplatin and oxaliplatin, as well as controlled narcotics, including fentanyl and tramadol. Our results indicate that race and ethnicity, while imprecise proxies for genetic diversity, correlate with patterns of pharmacogenomic variation in a way that is clearly relevant to medical treatment decisions. The effects of this variation is particularly pronounced for Black and Hispanic minority groups, owing to genetic differences from the majority White group. Treatment decisions that are made based on (assumed) White pharmacogenomic variant frequencies can be harmful for minority groups. Ignoring clinically relevant genetic differences among racial and ethnic groups, however well-intentioned, will exacerbate rather than ameliorate health disparities.

Pharmacogenomic biomarkers as source of evidence of the effectiveness and safety of antidepressant therapy

OBJECTIVE

The main goal of this work was to identify, describe, characterize, and classify the scientific evidence regarding the use of pharmacogenomic biomarkers in antidepressant treatment.

METHODS

The work was developed in two phases: i) a search for pharmacogenomic biomarkers in summaries of antidepressant drugs with marketing authorization in Portugal; and ii) a systematic literature review based on the data obtained in the first phase, with the main objective of finding international literature that could describe and characterize previously reported biomarkers and identify other relevant biomarkers. Finally, the levels of evidence and recommendation grades were classified.

RESULTS

Among the 26 drugs with marketing authorization in Portugal, only 16 had pharmacogenomic information. The most widely studied pharmacogenomic biomarker was CYP2D6. These results were mostly supported by the systematic literature review, which yielded 103 papers, 63 of which were ultimately included in the review. The systematic literature review also revealed the existence of other relevant biomarkers. Most of the included studies show a good level of evidence, which guarantees reliability and good recommendation grades. For the database (built during phase i), the results were informative but resulted in no specific recommendations.

CONCLUSIONS

Most pharmacogenomic variants are not studied or acknowledged by genetic tests, and more scientific research is needed to confirm their usefulness. Therefore, only a small number of variants are considered when prescribing antidepressant drugs. In addition, genotyping of patients is not common in clinical practice.

Characterizing pharmacogenetic programs using the consolidated framework for implementation research: A structured scoping review

Several healthcare organizations have developed pre-emptive pharmacogenetic testing programs, where testing is undertaken prior to the prescription of a medicine. This review characterizes the barriers and facilitators which influenced the development of these programs. A bidirectional citation searching strategy identified relevant publications before a standardized data extraction approach was applied. Publications were grouped by program and data synthesis was undertaken using the Consolidated Framework for Implementation Research (CFIR). 104 publications were identified from 40 programs and 4 multi-center initiatives. 26 (66%) of the programs were based in the United States and 95% in high-income countries. The programs were heterogeneous in their design and scale. The Characteristics of the Intervention, Inner Setting, and Process domains were referenced by 92.5, 80, and 77.5% of programs, respectively. A positive institutional culture, leadership engagement, engaging stakeholders, and the use of clinical champions were frequently described as facilitators to implementation. Clinician self-efficacy, lack of stakeholder knowledge, and the cost of the intervention were commonly cited barriers. Despite variation between the programs, there were several similarities in approach which could be categorized via the CFIR. These form a resource for organizations planning the development of pharmacogenetic programs, highlighting key facilitators which can be leveraged to promote successful implementation.

A blockchain-based framework to support pharmacogenetic data sharing

The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue. The design requirements for PGxChain were identified through a systematic literature review, identifying technical challenges and barriers impeding the clinical implementation of pharmacogenomics. These requirements included security and privacy, accessibility, interoperability, traceability and legal compliance. A proof-of-concept implementation based on Ethereum was then developed that met the design requirements. PGxChain's performance was examined using Hyperledger Caliper for latency, throughput, and transaction success rate. The findings clearly indicate that blockchain technology offers considerable potential to advance pharmacogenetic data sharing, particularly with regard to PGx data security and privacy, large-scale accessibility of PGx data, PGx data interoperability between multiple health care providers and compliance with data-sharing laws and regulations.

Implementation of HLA-B*15:02 Genotyping as Standard-of-Care for Reducing Carbamazepine/Oxcarbazepine Induced Cutaneous Adverse Drug Reactions in Thailand

Objective: This study aimed to investigate the clinical impact of HLA-B*15:02 pharmacogenomics (PGx) testing before carbamazepine (CBZ)/oxcarbazepine (OXC) prescriptions and to determine whether this PGx testing was associated with the reduction of CBZ/OXC-induced cutaneous adverse drug reactions (CADRs) in Thailand.

Methods: This retrospective observational cohort study was conducted by obtaining relevant HLA-B*15:02 PGx-testing and clinical data from electronic medical records during 2011–2020. 384 patient data were included in this study to investigate the clinical decision on CBZ/OXC usage before and after the HLA-B*15:02 PGx testing, and 1,539 patient data were included in this study to demonstrate the incidence of CBZ/OXC-induced SCARs and SJS between HLA-B*15:02 tested and non-tested patients. To analyze and summarize the results, descriptive statistics were employed, and Fisher exact test was used to compare the clinical difference between the HLA-B*15:02 positive and negative groups and to compare the differences of SCARs incidence.

Results: 384 patients were included in this study as per the inclusion criteria. Of these, 70 patients carried HLA-B*15:02, of which 63 and 65 patients were not prescribed with CBZ/OXC before and after the availability of genotyping results, respectively. In the remaining HLA-B*15:02 non-carriers, 48, and 189 patients were prescribed CBZ/OXC before and after genotyping results were available, respectively. The findings of this study showed that the incidence of SCARs of CBZ/OXC was significantly lower (p &lt; 0.001) in the HLA-B*15:02 screening arm than in the non-screening arm.

Conclusion:HLA-B pharmacogenetics testing influenced the selection of appropriate AEDs. The presence of mild rash in the HLA-B*15:02 negative group indicates that other genetic biomarker (HLA-A*31:01) and/or non-genetic variables are involved in CBZ/OXC-induced CADRs, emphasizing that CBZ/OXC prescriptions necessitate CADR monitoring. The hospital policy and clinical decision support (CDS) alert system is essential to overcome the barriers associated with the utilization of PGx guidelines into clinical practice.

Population genetic polymorphisms of pharmacogenes in Zimbabwe, a potential guide for the safe and efficacious use of medicines in people of African ancestry

OBJECTIVE

Pharmacogenomics (PGx) is a clinically significant factor in the safe and efficacious use of medicines. While PGx knowledge is abundant for other populations, there are scarce PGx data on African populations and is little knowledge on drug-gene interactions for medicines used to treat diseases common in Africa. The aim of this study was to use a custom-designed open array to genotype clinically actionable variants in a Zimbabwean population. This study also identified some of the commonly used drugs in Zimbabwe and the associated genes involved in their metabolism.

METHODS

A custom-designed open array that covers 120 genetic variants was used to genotype 522 black Zimbabwean healthy volunteers using TaqMan-based single nucleotide polymorphism genotyping. Data were also accessed from Essential Drugs' List in Zimbabwe (EDLIZ), and the medicines were grouped into the associated biomarker groups based on their metabolism. We also estimated the national drug procurement levels for medicines that could benefit from PGx-guided use based on the data obtained from the national authorities in Zimbabwe.

RESULTS

The results demonstrate the applicability of an open-array chip in simultaneously determining multiple genetic variants in an individual, thus significantly reducing cost and time to generate PGx data. There were significantly high frequencies of African-specific variants, such as the CYP2D6*17 and *29 variants and the CYP2B6*18 variant. The data obtained showed that the Zimbabwean population exhibits PGx variations in genes important for the safe and efficacious use of drugs approved by the EDLIZ and are procured at significantly large amounts annually. The study has established a cohort of genotyped healthy volunteers that can be accessed and used in the conduct of clinical pharmacogenetic studies for drugs entering a market of people of predominantly African ancestry.

CONCLUSION

Our study demonstrated the potential benefit of integrating PGx in Zimbabwe for the safe and efficacious use of drugs that are commonly used.

Digital tools for the assessment of pharmacological treatment for depressive disorder: State of the art

Depression is an invalidating disorder, marked by phenotypic heterogeneity. Clinical assessments for treatment adjustments and data-collection for pharmacological research often rely on subjective representations of functioning. Better phenotyping through digital applications may add unseen information and facilitate disentangling the clinical characteristics and impact of depression and its pharmacological treatment in everyday life. Researchers, physicians, and patients benefit from well-understood digital phenotyping approaches to assess the treatment efficacy and side-effects. This review discusses the current possibilities and pitfalls of wearables and technology for the assessment of the pharmacological treatment of depression. Their applications in the whole spectrum of treatment for depression, including diagnosis, treatment of an episode, and monitoring of relapse risk and prevention are discussed. Multiple aspects are to be considered, including concerns that come with collecting sensitive data and health recordings. Also, privacy and trust are addressed. Available applications range from questionnaire-like apps to objective assessment of behavioural patterns and promises in handling suicidality. Nonetheless, interpretation and integration of this high-resolution information with other phenotyping levels, remains challenging. This review provides a state-of-the-art description of wearables and technology in digital phenotyping for monitoring pharmacological treatment in depression, focusing on the challenges and opportunities of its application in clinical trials and research.

Clinical Implementation of DPYD Pharmacogenetic Testing to Prevent Early-Onset Fluoropyrimidine-Related Toxicity in Cancer Patients in Switzerland

The implementation of pharmacogenetic testing into clinical practice has been a slow process so far. Here, we review the implementation of pre-treatment testing of dihydropyrimidine dehydrogenase gene (DPYD) risk variants to prevent early-onset fluoropyrimidine (FP)-related toxicity in cancer patients in Switzerland based on data of a large Swiss diagnostic center. In January 2017, the Swiss Federal Office of Public Health introduced the reimbursement of DPYD testing by the compulsory health insurance in Switzerland based on evidence for the clinical relevance of DPYD-risk variants and the cost-effectiveness of pre-treatment testing, and on the availability of international guidelines. However, we did not observe a strong increase in DPYD testing at our diagnostic center from 2017 to 2019. Only a low number of DPYD-testing requests (28-42 per year), concerning mostly retrospective investigations of suspected FP-toxicity, were received. In contrast, we observed a 14-fold increase in DPYD testing together with a strong shift from retrospective to pre-treatment test requests upon the release of recommendations for DPYD testing prior to FP-treatment in April 2020 by the European Medicines Agency. This increase was mainly driven by three geographic regions of Switzerland, where partner institutions of previous research collaborations regarding FP-related toxicity are located and who acted as early-adopting institutions of DPYD testing. Our data suggest the important role of early adopters as accelerators of clinical implementation of pharmacogenetic testing by introducing these policies to their working environment and educating health workers from their own and nearby institutions.

The Identification of Novel CYP2D6 Variants in US Hmong: Results From Genome Sequencing and Clinical Genotyping

Objective: Hmong individuals represent a unique East Asian subpopulation in whom limited information concerning pharmacogenetic variation exists. The objectives of this study were to comprehensively characterize the highly polymorphic CYP2D6 gene in Hmong, estimate allele and phenotype frequencies and to compare results between two testing platforms. Methods: DNA from 48 self-identified Hmong participants were sequenced using a targeted next-generation sequencing (NGS) panel. Star allele calls were made using Astrolabe, manual inspection of NGS variant calls and confirmatory Sanger sequencing. Structural variation was determined by long-range (XL)-PCR and digital droplet PCR (ddPCR). The consensus diplotypes were subsequently translated into phenotype utilizing the activity score system. Clinical grade pharmacogenetic testing was obtained for 12 of the 48 samples enabling an assessment of concordance between the consensus calls and those determined by clinical testing platforms. Results: A total of 13 CYP2D6 alleles were identified. The most common alleles were CYP2D6*10 and its structural arrangements (37.5%, 36/96) and the *5 gene deletion (13.5%, 13/96). Three novel suballeles (*10.007, *36.004, and *75.002) were also identified. Phenotype frequencies were as follows: ultrarapid metabolizers (4.2%, 2/48), normal metabolizers (41.7%, 20/48) and intermediate metabolizers (52.1%, 25/48); none of the 48 participants were predicted to be poor metabolizers. Concordance of diplotype and phenotype calls between the consensus and clinical testing were 66.7 and 50%, respectively. Conclusion: Our study to explore CYP2D6 genotypes in the Hmong population suggests that this subpopulation is unique regarding CYP2D6 allelic variants; also, a higher portion of Hmong participants (50%) are predicted to have an intermediate metabolizer phenotype for CYP2D6 compared to other East Asians which range between 27 and 44%. Results from different testing methods varied considerably. These preliminary findings underscore the importance of thoroughly interrogating unique subpopulations to accurately predict a patient's CYP2D6 metabolizer status.

Analysis of a panel-based pharmacogenomics testing program among members of a commercial and Medicare client of a pharmacy benefits manager

BACKGROUND: Although the field of pharmacogenomics (PGx) has existed for decades, use of pharmacogenomic information by providers to optimize medication therapy for patients has had relatively slow adoption. There are many factors that have contributed to the slow adoption of PGx testing, but it is partially due to a lack of coverage by payers. If PGx testing is covered by payers, frequently only testing of a specific gene is covered, rather than a panel of many genes. As a result, little is known about how coverage of a panel-based PGx test will affect a member's medication therapy. OBJECTIVES: To determine how giving providers specific medication optimization recommendations, based on results of a panel-based PGx test, impacted members' medication regimens. METHODS: Pharmacy claims data were retrospectively reviewed for this exploratory study. Members who participated in PGx testing were in the intervention group and members who chose not to participate in the PGx testing, but who were eligible to participate, were in the control group. PGx test results, including suggested medication changes, were mailed to providers. To determine if providers adopted the suggested medication changes, pharmacy claims data were analyzed retrospectively for the 4-month period preceding and following the date from which recommendations were provided to prescribers. RESULTS: Of the 101 members included in the analysis, 50 were in the intervention group and 51 were in the control group. In the intervention group, members were taking in a total of 352 medications; 165 of the medications had PGx guidance. Based on the PGx test results, 62 of these medications (37.6%) had recommendations. Of members who received PGx testing, 76% had at least 1 recommended change. When pharmacist recommendations were made, a change was made to the medication 27% of the time. There was a statistically significant difference between the number of medication changes in the PGx group and the control group (P = 0.024). CONCLUSIONS: Recommendations based on PGx testing can lead to changes in medications and an optimized medication regimen for members. DISCLOSURES: The authors have no conflicts to disclose that may present a potential conflict of interest.

Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review

Conventional medicines optimisation interventions in people with multimorbidity and polypharmacy are complex and yet limited; a more holistic and integrated approach to healthcare delivery is required. Pharmacogenetics has potential as a component of medicines optimisation. Studies involving multi-medicine pharmacogenetics in adults with multimorbidity or polypharmacy, reporting on outcomes derived from relevant core outcome sets, were included in this systematic review. Narrative synthesis was undertaken to summarise the data; meta-analysis was inappropriate due to study heterogeneity. Fifteen studies of diverse design and variable quality were included. A small, randomised study involving pharmacist-led medicines optimisation, including pharmacogenetics, suggests this approach could have significant benefits for patients and health systems. However, due to study design heterogeneity and the quality of the included studies, it is difficult to draw generalisable conclusions. Further pragmatic, robust pharmacogenetics studies in diverse, real-world patient populations, are required to establish the benefit of multi-medicine pharmacogenetic screening on patient outcomes.

The Value of Pharmacogenetics to Reduce Drug-Related Toxicity in Cancer Patients

Many anticancer drugs cause adverse drug reactions (ADRs) that negatively impact safety and reduce quality of life. The typical narrow therapeutic range and exposure-response relationships described for anticancer drugs make precision dosing critical to ensure safe and effective drug exposure. Germline mutations in pharmacogenes contribute to inter-patient variability in pharmacokinetics and pharmacodynamics of anticancer drugs. Patients carrying reduced-activity or loss-of-function alleles are at increased risk for ADRs. Pretreatment genotyping offers a proactive approach to identify these high-risk patients, administer an individualized dose, and minimize the risk of ADRs. In the field of oncology, the most well-studied gene-drug pairs for which pharmacogenetic dosing recommendations have been published to improve safety are DPYD-fluoropyrimidines, TPMT/NUDT15-thiopurines, and UGT1A1-irinotecan. Despite the presence of these guidelines, the scientific evidence showing the benefits of pharmacogenetic testing (e.g., improved safety and cost-effectiveness) and the development of efficient multi-gene genotyping panels, routine pretreatment testing for these gene-drug pairs has not been implemented widely in the clinic. Important considerations required for widespread clinical implementation include pharmacogenetic education of physicians, availability or allocation of institutional resources to build an efficient clinical infrastructure, international standardization of guidelines, uniform adoption of guidelines by regulatory agencies leading to genotyping requirements in drug labels, and development of cohesive reimbursement policies for pretreatment genotyping. Without clinical implementation, the potential of pharmacogenetics to improve patient safety remains unfulfilled.

Comparison of FDA Table of Pharmacogenetic Associations and Clinical Pharmacogenetics Implementation Consortium guidelines

Purpose

Healthcare professionals need a clear understanding of information about gene-drug interactions in order to make optimal use of pharmacogenetic (PGx) testing. In this report, we compare PGx information in the US Food and Drug Administration (FDA) Table of Pharmacogenetic Associations with information presented in Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines.

Summary

Information from CPIC guidelines and the FDA Table of Pharmacogenetic Associations do not have a high level of concordance. Many drugs mentioned in CPIC guidelines are not listed in the FDA table and vice versa, and the same gene-drug association and dosing recommendation was reported for only 5 of the 126 drugs included in either source. Furthermore, classification of drugs in specific sections of the FDA table does not correlate well with CPIC-assigned or provisionally assigned clinical actionability levels. The Pharmacogenomics Knowledge Base (PharmGKB) clinical annotation levels are generally high for drugs mentioned in CPIC guidelines. PharmGKB clinical annotation levels are often unassigned or are lower level for drugs listed on the FDA table but not in CPIC guidelines. These differences may be due in part to FDA having access to PGx information that is unavailable in published literature and/or because PGx classifications are based on criteria other than clinical actionability.

Conclusion

There are important differences between the PGx information presented in the FDA Table of Pharmacogenetic Associations and in CPIC guidelines. FDA and CPIC have different perspectives when evaluating PGx associations and use different approaches and information resources when considering clinical validity related to specific medicines. Understanding how information sources developed by each group differ and can be used together to form a holistic view of PGx may be helpful in increasing adoption of these information sources in practice.

From Pharmacogenetics to Pharmaco-Omics:Milestones and Future Directions

The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.

Pharmacogenomics of Pediatric Cardiac Arrest: Cisplatin Treatment Worsened by a Ryanodine Receptor 2 Gene Mutation

In thelast few decades, the roles of cardio-oncology and cardiovascular geneticsgained more and more attention in research and daily clinical practice, shaping a new clinical approach and management of patients affected by cancer and cardiovascular disease. Genetic characterization of patients undergoing cancer treatment can support a better cardiovascular risk stratification beyond the typical risk factors, suchas contractile function and QT interval duration, uncovering a possible patient’s concealed predisposition to heart failure, life threatening arrhythmias and sudden death. Specifically, an integrated cardiogenetic approach in daily oncological clinical practice can ensure the best patient-centered healthcare model, suggesting, also the adequate cardiac monitoring timing and alternative cancer treatments, reducing drug-related complications. We report the case of a 14-month-old girl affected by neuroblastoma, treated by cisplatin, complicated by cardiac arrest. We described the genetic characterization of a Ryanodine receptor 2 (RYR2) gene mutation and subsequent pharmacogenomic approach to better shape the cancer treatment.

Perspectives from the Society for Pediatric Research: pharmacogenetics for pediatricians

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

Pharmacogenetic Testing Knowledge and Attitudes among Pediatric Psychiatrists and Pediatricians in Alberta, Canada

OBJECTIVE

To assess knowledge, attitudes, and barriers as well as ethical, legal and social concerns towards pharmacogenetic (PGx) testing among pediatric psychiatrists and pediatricians in Alberta, Canada.

METHOD

An anonymous electronic survey was sent to pediatric psychiatrists (n = 49) and pediatricians (n = 93) in Alberta.

RESULTS

A total of 20 surveys were completed (response rate = 14%). Respondents agreed that PGx testing is clinically useful and a majority believed testing had the potential to aid in medication selection, dosing, switching, augmentation, and deprescribing, particularly among children with treatment-resistant conditions. However, most respondents could not identify an appropriate lab to perform testing, did not have the necessary training to interpret PGx results, and did not have access to experts that could assist them in interpreting results.

CONCLUSION

The findings suggest additional PGx education and training is required to boost self-efficacy and uptake of PGx testing among pediatric psychiatrists and pediatricians in Alberta, Canada. In addition, local and global efforts to develop clinical practice guidelines, provide clear legal guidance, and ensure equitable access to testing may facilitate the implementation of PGx-informed prescribing.

Pharmacist assessment of drug-gene interactions and drug-induced phenoconversion in major depressive disorder: a case report

BACKGROUND

Response to antidepressant therapy is highly variable among individuals. Pharmacogenomic (PGx) testing presents an opportunity to guide drug selection while optimizing therapy outcomes and/or decreasing the risk for toxicity.

CASE PRESENTATION

A patient with multiple comorbidities, including severe major depressive disorder (MDD), experienced adverse drug events and undesirable response to multiple antidepressant medications (i.e., bupropion, escitalopram, and venlafaxine). A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions as well as other clinical factors to provide recommendations for antidepressant therapy optimization.

CONCLUSION

This case highlights the importance of PGx testing and the key role of pharmacists in identifying and mitigating drug-related problems and optimizing drug therapy in patients with MDD.