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

Establishing the Medical Actionability of Genomic Variants

Actionability is an important concept in medicine that does not have a well-accepted standard definition, nor is there a general consensus on how to establish it. Medical actionability is often conflated with clinical utility, a related but distinct concept. This lack of clarity contributes to practice variation and inconsistent coverage decisions in genomic medicine, leading to the potential for systematic bias in the use of evidence-based interventions. We clarify how medical actionability and clinical utility are distinct and then discuss the spectrum of actionability, including benefits for the person, the family, and society. We also describe applications across the life course, including prediction, diagnosis, and treatment. Current challenges in assessing the medical actionability of identified genomic variants include gaps in the evidence, limited contexts with practice guidelines, and subjective aspects of medical actionability. A standardized and authoritative assessment of medical actionability is critical to implementing genomic medicine in a fashion that improves population health outcomes and reduces health disparities. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Automated Pharmacogenomic Reports for Clinical Genome Sequencing

Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing that could help inform medication selection or dosing throughout the lifespan. Implementation of pharmacogenomic reporting must address several challenges, including inherent limitations in short-read genome sequencing methods, gene and variant selection, standardization of genotype and phenotype nomenclature, and choice of guidelines and drugs to report. An automated pipeline, lmPGX, was developed as an end-to-end solution that produces two versions of a pharmacogenomic report, presenting either Clinical Pharmacogenetics Implementation Consortium or US Food and Drug Administration guidelines for 12 genes. The pipeline was validated for performance using reference samples and pharmacogenetic data from the Genetic Testing Reference Materials Coordination Program. To determine performance and limitations, lmPGX was compared with three additional publicly available pharmacogenomic pipelines. The lmPGX pipeline offers clinical laboratories an opportunity for seamless integration of pharmacogenomic results with genome reporting.

CYP1A2 mRNA Expression Rather than Genetic Variants Indicate Hepatic CYP1A2 Activity

CYP1A2, one of the most abundant hepatic cytochrome P450 enzymes, is involved in metabolism of several drugs and carcinogenic compounds. Data on the significance of CYP1A2 genetic polymorphisms in enzyme activity are highly inconsistent; therefore, the impact of CYP1A2 genetic variants (−3860G>A, −2467delT, −739T>G, −163C>A, 2159G>A) on mRNA expression and phenacetin O-dealkylation selective for CYP1A2 was investigated in human liver tissues and in psychiatric patients belonging to Caucasian populations. CYP1A2*1F, considered to be associated with high CYP1A2 inducibility, is generally identified by the presence of −163C>A polymorphism; however, we demonstrated that −163C>A existed in several haplotypes (CYP1A2*1F, CYP1A2*1L, CYP1A2*1M, CYP1A2*1V, CYP1A2*1W), and consequently, CYP1A2*1F was a much rarer allelic variant (0.4%) than reported in Caucasian populations. Of note, −163C>A polymorphism was found to result in an increase of neither mRNA nor the activity of CYP1A2. Moreover, hepatic CYP1A2 activity was associated with hepatic or leukocyte mRNA expression rather than genetic polymorphisms of CYP1A2. Consideration of non-genetic phenoconverting factors (co-medication with CYP1A2-specific inhibitors/inducers, tobacco smoking and non-specific factors, including amoxicillin+clavulanic acid therapy or chronic alcohol consumption) did not much improve genotype−phenotype estimation. In conclusion, CYP1A2-genotyping is inappropriate for the prediction of CYP1A2 function; however, CYP1A2 mRNA expression in leukocytes can inform about patients’ CYP1A2-metabolizing capacity.

Clinical Practice Guidelines Using GRADE and AGREE II for the Impact of Genetic Variants on Plasma Lipid/Lipoprotein/Apolipoprotein Responsiveness to Omega-3 Fatty Acids

Background

A recent systematic review, which used the GRADE methodology, concluded that there is strong evidence for two gene-diet associations related to omega-3 and plasma triglyceride (TG) responses. Systematic reviews can be used to inform the development of clinical practice guidelines (CPGs).

Objective

To provide guidance for clinical practice related to genetic testing for evaluating responsiveness to dietary/supplemental omega-3s and their impact on plasma lipids/lipoproteins/apolipoproteins.

Design

Using the results of the abovementioned systematic review, the first CPGs in nutrigenetics were developed using the established GRADE methodology and AGREE II approach.

Results

Three clinical practice recommendations were developed. Most gene-diet associations identified in the literature lack adequate scientific and clinical validity to warrant consideration for implementing in a practice setting. However, two gene-diet associations with strong evidence (GRADE quality: moderate and high) can be considered for implementation into clinical practice in certain cases: male APOE-E4 carriers (rs429358, rs7412) and TG changes in response to the omega-3 fatty acids eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA) as well as a 31-SNP nutrigenetic risk score and TG changes in response to EPA+DHA among adults with overweight/obesity. Ethical and regulatory implications must be considered when providing APOE nutrigenetic tests given the well-established link between APOE genetic variation and Alzheimer's Disease.

Conclusion

Most of the evidence in this area is not ready for implementation into clinical practice primarily due to low scientific validity (low quality of evidence). However, the first CPGs in nutrigenetics have been developed for two nutrigenetic associations with strong scientific validity, related to dietary/supplemental omega-3 and TG responses.

DNA Genotyping Based on Isothermal Amplification and Colorimetric Detection by Consumer Electronics Devices

The point-of-care testing of DNA biomarkers requires compact biosensing systems and consumer electronic technologies provide fascinating opportunities. Their portability, mass-produced components, and high-performance readout capabilities are the main advantages for the development of novel bioanalytical methods.This chapter describes the detection of single nucleotide polymorphisms (SNP) through methods based on user-friendly optical devices (e.g., USB digital microscope, flatbed scanner, smartphone, and DVD drive). Loop mediated isothermal amplification (LAMP) enables the required discrimination of each specific variant prior to the optical reading. In the first method, products are directly hybridized to the allele-specific probes attached to plastic chips in an array format. The second method, allele-specific primers are used, enabling the direct end-point detection based a colorimetric dyer and a microfluidic chamber chip. In both approaches, devices are employed for chip scanning.A representative application to the genotyping of a clinically relevant SNP from human samples is provided, showing the excellent features achieved. Consumer electronic devices are able to register sensitive precise measurements in terms of signal-to-noise ratios, image resolution, and scan-to-scan reproducibility. The integrated DNA-based method lead a low detection limit (100 genomic DNA copies), reproducible (variation <15%), high specificity (genotypes validated by reference method), and cheap assays (<10 €/test). The underlying challenge is the reliable implementation into minimal-specialized clinical laboratories, incorporating additional advantages, such as user-friendly interface, low cost, and connectivity for telemedicine needs.

Gene-drug pairings for antidepressants and antipsychotics: level of evidence and clinical application

Substantial inter-individual discrepancies exist in both therapeutic effectiveness and adverse effects of antidepressant and antipsychotic medications, which can, in part, be explained by genetic variation. Here, we searched the Pharmacogenomics Knowledge Base for gene-antidepressant and gene-antipsychotic pairs with the highest level of evidence. We then extracted and compared the associated prescribing recommendations for these pairs developed by the Clinical Pharmacogenomics Implementation Consortium, the Dutch Pharmacogenetics Working Group or approved product labels in the US, Canada, Europe, and Asia. Finally, we highlight key economical, educational, regulatory, and ethical issues that, if not appropriately considered, can hinder the implementation of these recommendations in clinical practice. Our review indicates that evidence-based guidelines are available to assist with the implementation of pharmacogenetic-guided antidepressant and antipsychotic prescribing, although the maximum impact of these guidelines on patient care will not be realized until key barriers are minimized or eliminated.

An Investigation of the Knowledge Overlap between Pharmacogenomics and Disease Genetics

Precision medicine faces many challenges, including the gap of knowledge between disease genetics and pharmacogenomics (PGx). Disease genetics interprets the pathogenicity of genetic variants for diagnostic purposes, while PGx investigates the genetic influences on drug responses. Ideally, the quality of health care would be improved from the point of disease diagnosis to drug prescribing if PGx is integrated with disease genetics in clinical care. However, PGx genes or variants are usually not reported as a secondary finding even if they are included in a clinical genetic test for diagnostic purposes. This happens even though the detection of PGx variants can provide valuable drug prescribing recommendations. One underlying reason is the lack of systematic classification of the knowledge overlap between PGx and disease genetics. Here, we address this issue by analyzing gene and genetic variant annotations from multiple expert-curated knowledge databases, including PharmGKB, CPIC, ClinGen and ClinVar. We further classified genes based on the strength of evidence supporting a gene's pathogenic role or PGx effect as well as the level of clinical actionability of a gene. Twenty-six genes were found to have pathogenic variation associated with germline diseases as well as strong evidence for a PGx association. These genes were classified into four sub-categories based on the distinct connection between the gene's pathogenic role and PGx effect. Moreover, we have also found thirteen RYR1 genetic variants that were annotated as pathogenic and at the same time whose PGx effect was supported by a preponderance of evidence and given drug prescribing recommendations. Overall, we identified a nontrivial number of gene and genetic variant overlaps between disease genetics and PGx, which laid out a foundation for combining PGx and disease genetics to improve clinical care from disease diagnoses to drug prescribing and adherence.

Understanding the barriers and enablers of pharmacogenomic testing in primary care: a qualitative systematic review with meta-aggregation synthesis

Introduction: Pharmacogenomic testing can indicate which drugs may have limited therapeutic action or lead to adverse effects, hence guiding rational and safe prescribing. However, in the UK and other countries, there are still significant barriers to implementation of testing in primary care. Objective: This systematic review presents the barriers and enablers to the implementation of pharmacogenomics in primary care setting. Materials & methods: MEDLINE, EMBASE, PsycINFO and CINAHL databases were searched through to July 2020 for studies that reported primary qualitative data of primary care professionals and patient views. Following screening, data extraction and quality assessment, data synthesis was undertaken using meta-aggregation based on the theoretical domain's framework (TDF). Confidence in the synthesized findings relating to credibility and dependability was established using CONQual. Eligible papers were categorized into six TDF domains - knowledge; social and professional roles; behavioral regulation; beliefs and consequences; environmental context and resources; and social influences. Results: From 1669 citations, eighteen eligible studies were identified across seven countries, with a sample size of 504 participants including both primary care professionals and patients. From the data, 15 synthesized statements, all with moderate CONQual rating emerged. These categories range from knowledge, awareness among Primary Care Physicians and patients, professional relationships, negative impact of PGx, belief that PGx can reduce adverse drug reactions, clinical evidence, cost-effectiveness, informatics, reporting issues and social issues. Conclusion: Through use of TDF, fifteen synthesized statements provide policymakers with valuable recommendations for the implementation of pharmacogenomics in primary care. In preparation, policymakers need to consider the introduction of effective educational strategies for both PCPs and patients to raise knowledge, awareness, and engagement. The actual introduction of PGx will require reorganization with decision support tools to aid use of PGx in primary care, with a clear delegation of roles and responsibilities between general professionals and pharmacists supplemented by a local pool of experts. Furthermore, policy makers need to address the cost effectiveness of pharmacogenomics and having appropriate infrastructure supporting testing and interpretation including informatic solutions for utilizing pharmacogenomic results.

Man vs. machine: comparison of pharmacogenetic expert counselling with a clinical medication support system in a study with 200 genotyped patients

Background

Medication problems such as strong side effects or inefficacy occur frequently. At our university hospital, a consultation group of specialists takes care of patients suffering from medication problems. Nevertheless, the counselling of poly-treated patients is complex, as it requires the consideration of a large network of interactions between drugs and their targets, their metabolizing enzymes, and their transporters, etc.

Purpose

This study aims to check whether a score-based decision-support system (1) reduces the time and effort and (2) suggests solutions at the same quality level.

Patients and methods

A total of 200 multimorbid, poly-treated patients with medication problems were included. All patients were considered twice: manually, as clinically established, and using the Drug-PIN decision-support system. Besides diagnoses, lab data (kidney, liver), phenotype (age, gender, BMI, habits), and genotype (genetic variants with actionable clinical evidence I or IIa) were considered, to eliminate potentially inappropriate medications and to select individually favourable drugs from existing medication classes. The algorithm is connected to automatically updated knowledge resources to provide reproducible up-to-date decision support.

Results

The average turnaround time for manual poly-therapy counselling per patient ranges from 3 to 6 working hours, while it can be reduced to ten minutes using Drug-PIN. At the same time, the results of the novel computerized approach coincide with the manual approach at a level of > 90%. The holistic medication score can be used to find favourable drugs within a class of drugs and also to judge the severity of medication problems, to identify critical cases early and automatically.

Conclusion

With the computerized version of this approach, it became possible to score all combinations of all alternative drugs from each class of drugs administered (“personalized medication landscape “) and to identify critical patients even before problems are reported (“medication alert”). Careful comparison of manual and score-based results shows that the incomplete manual consideration of genetic specialties and pharmacokinetic conflicts is responsible for most of the (minor) deviations between the two approaches. The meaning of the reduction of working time for experts by about 2 orders of magnitude should not be underestimated, as it enables practical application of personalized medicine in clinical routine.

A Systematic Review and Recommendations Around Frameworks for Evaluating Scientific Validity in Nutritional Genomics

Background: There is a significant lack of consistency used to determine the scientific validity of nutrigenetic research. The aims of this study were to examine existing frameworks used for determining scientific validity in nutrition and/or genetics and to determine which framework would be most appropriate to evaluate scientific validity in nutrigenetics in the future.

Methods: A systematic review (PROSPERO registration: CRD42021261948) was conducted up until July 2021 using Medline, Embase, and Web of Science, with articles screened in duplicate. Gray literature searches were also conducted (June-July 2021), and reference lists of two relevant review articles were screened. Included articles provided the complete methods for a framework that has been used to evaluate scientific validity in nutrition and/or genetics. Articles were excluded if they provided a framework for evaluating health services/systems more broadly. Citing articles of the included articles were then screened in Google Scholar to determine if the framework had been used in nutrition or genetics, or both; frameworks that had not were excluded. Summary tables were piloted in duplicate and revised accordingly prior to synthesizing all included articles. Frameworks were critically appraised for their applicability to nutrigenetic scientific validity assessment using a predetermined categorization matrix, which included key factors deemed important by an expert panel for assessing scientific validity in nutrigenetics.

Results: Upon screening 3,931 articles, a total of 49 articles representing 41 total frameworks, were included in the final analysis (19 used in genetics, 9 used in nutrition, and 13 used in both). Factors deemed important for evaluating nutrigenetic evidence related to study design and quality, generalizability, directness, consistency, precision, confounding, effect size, biological plausibility, publication/funding bias, allele and nutrient dose-response, and summary levels of evidence. Frameworks varied in the components of their scientific validity assessment, with most assessing study quality. Consideration of biological plausibility was more common in frameworks used in genetics. Dose-response effects were rarely considered. Two included frameworks incorporated all but one predetermined key factor important for nutrigenetic scientific validity assessment.

Discussion/Conclusions: A single existing framework was highlighted as optimal for the rigorous evaluation of scientific validity in nutritional genomics, and minor modifications are proposed to strengthen it further.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=261948, PROSPERO [CRD42021261948].

The Contribution of Pharmacogenetic Drug Interactions to 90-Day Hospital Readmissions: Preliminary Results from a Real-World Healthcare System

Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines exist for many medications commonly prescribed prior to hospital discharge, yet there are limited data regarding the contribution of gene-x-drug interactions to hospital readmissions. The present study evaluated the relationship between prescription of CPIC medications prescribed within 30 days of hospital admission and 90-day hospital readmission from 2010 to 2020 in a study population (N = 10,104) who underwent sequencing with a 14-gene pharmacogenetic panel. The presence of at least one pharmacogenetic indicator for a medication prescribed within 30 days of hospital admission was considered a gene-x-drug interaction. Multivariable logistic regression analyzed the association between one or more gene-x-drug interactions with 90-day readmission. There were 2211/2354 (93.9%) admitted patients who were prescribed at least one CPIC medication. Univariate analyses indicated that the presence of at least one identified gene-x-drug interaction increased the risk of 90-day readmission by more than 40% (OR = 1.42, 95% confidence interval (CI) 1.09–1.84) (p = 0.01). A multivariable model adjusting for age, race, sex, employment status, body mass index, and medical conditions slightly attenuated the effect (OR = 1.32, 95% CI 1.02–1.73) (p = 0.04). Our results suggest that the presence of one or more CPIC gene-x-drug interactions increases the risk of 90-day hospital readmission, even after adjustment for demographic and clinical risk factors.

Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System

Pharmacogenomics (PGx) studies how a person's genes affect the response to medications and is quickly becoming a significant part of precision medicine. The clinical application of PGx principles has consistently been cited as a major opportunity for improving therapeutic outcomes. Several recent studies have demonstrated that most individuals (> 90%) harbor PGx variants that would be clinically actionable if prescribed a medication relevant to that gene. In multiple well-conducted studies, the results of PGx testing have been shown to guide therapy choice and dosing modifications which improve treatment efficacy and reduce the incidence of adverse drug reactions (ADRs). Although the value of PGx testing is evident, its successful implementation in a clinical setting presents a number of challenges to molecular diagnostic laboratories, healthcare systems, providers and patients. Different molecular methods can be applied to identify PGx variants and the design of the assay is therefore extremely important. Once the genotyping results are available the biggest technical challenge lies in turning this complex genetic information into phenotypes and actionable recommendations that a busy clinician can effectively utilize to provide better medical care, in a cost-effective, efficient and reliable manner. In this paper we describe a successful and highly collaborative implementation of the PGx testing program at the University of Minnesota and MHealth Fairview Molecular Diagnostic Laboratory and selected Pharmacies and Clinics. We offer detailed descriptions of the necessary components of the pharmacogenomic testing implementation, the development and technical validation of the in-house SNP based multiplex PCR based assay targeting 20 genes and 48 SNPs as well as a separate CYP2D6 copy number assay along with the process of PGx report design, results of the provider and pharmacists usability studies, and the development of the software tool for genotype-phenotype translation and gene-phenotype-drug CPIC-based recommendations. Finally, we outline the process of developing the clinical workflow that connects the providers with the PGx experts within the Molecular Diagnostic Laboratory and the Pharmacy.

Evaluation of the Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program at initial test sites

Aim: The first Plan-Do-Study-Act cycle for the Veterans Affairs Pharmacogenomic Testing for Veterans pharmacogenomic clinical testing program is described. Materials & methods: Surveys evaluating implementation resources and processes were distributed to implementation teams, providers, laboratory and health informatics staff. Survey responses were mapped to the Consolidated Framework for Implementation Research constructs to identify implementation barriers. The Expert Recommendation for Implementing Change strategies were used to address implementation barriers. Results: Survey response rate was 23-73% across personnel groups at six Veterans Affairs sites. Nine Consolidated Framework for Implementation Research constructs were most salient implementation barriers. Program revisions addressed these barriers using the Expert Recommendation for Implementing Change strategies related to three domains. Conclusion: Beyond providing free pharmacogenomic testing, additional implementation barriers need to be addressed for improved program uptake.

Impact of Updating Pharmacogenetic Results: Lessons Learned from the PREDICT Program

Pharmacogenomic (PGx) evidence for selective serotonin reuptake inhibitors (SSRIs) continues to evolve. For sites offering testing, maintaining up-to-date interpretations and implementing new clinical decision support (CDS) driven by existing results creates practical and technical challenges. Vanderbilt University Medical Center initiated panel testing in 2010, added CYP2D6 testing in 2017, and released CDS for SSRIs in 2020. We systematically reinterpreted historic CYP2C19 and CYP2D6 genotypes to update phenotypes to current nomenclature and to launch provider CDS and patient-oriented content for SSRIs. Chart review was conducted to identify and recontact providers caring for patients with current SSRI therapy and new actionable recommendations. A total of 15,619 patients’ PGx results were reprocessed. Of the non-deceased patients reprocessed, 21% (n = 3278) resulted in CYP2C19*1/*17 reinterpretations. Among 289 patients with an actionable recommendation and SSRI medication prescription, 31.8% (n = 92) did not necessitate contact of a clinician, while 43.2% (n = 125) resulted in clinician contacted, and for 25% (n = 72) no appropriate clinician was able to be identified. Maintenance of up-to-date interpretations and recommendations for PGx results over the lifetime of a patient requires continuous effort. Reprocessing is a key strategy for maintenance and expansion of PGx content to be periodically considered and implemented.

Development of the pharmacogenomics and genomics literacy framework for pharmacists

BACKGROUND

Pharmacists play a unique role in integrating genomic medicine and pharmacogenomics into the clinical practice and to translate pharmacogenomics from bench to bedside. However, the literature suggests that the knowledge gap in pharmacogenomics is a major challenge; therefore, developing pharmacists' skills and literacy to achieve this anticipated role is highly important. We aim to conceptualize a personalized literacy framework for the adoption of genomic medicine and pharmacogenomics by pharmacists in the United Arab Emirates with possible regional and global relevance.

RESULTS

A qualitative approach using focus groups was used to design and to guide the development of a pharmacogenomics literacy framework. The Health Literacy Skills framework was used as a guide to conceptualize the pharmacogenomics literacy for pharmacists. The framework included six major components with specific suggested factors to improve pharmacists' pharmacogenomics literacy. Major components include individual inputs, demand, skills, knowledge, attitude and sociocultural factors.

CONCLUSION

This framework confirms a holistic bottom-up approach toward the implementation of pharmacogenomics. Personalized medicine entails personalized efforts and frameworks. Similar framework can be created for other healthcare providers, patients and stakeholders.

Barriers to clinical adoption of pharmacogenomic testing in psychiatry: a critical analysis

Pharmacogenomics (PGx) is the study of genetic influences on an individual's response to medications. Improvements in the quality and quantity of PGx research over the past two decades have enabled the establishment of commercial markets for PGx tests. Nevertheless, PGx testing has yet to be adopted as a routine practice in clinical care. Accordingly, policy regulating the commercialization and reimbursement of PGx testing is in its infancy. Several papers have been published on the topic of challenges, or 'barriers' to clinical adoption of this healthcare innovation. However, many do not include recent evidence from randomized controlled trials, economic utility studies, and qualitative assessments of stakeholder opinions. The present paper revisits the most cited barriers to adoption of PGx testing: evidence for clinical utility, evidence for economic effectiveness, and stakeholder awareness. We consider these barriers in the context of reviewing PGx literature published over the past two decades and emphasize data from commercial PGx testing companies, since they have published the largest datasets. We conclude with a discussion of existing limitations to PGx testing and recommendations for progress.

Analytical validation of a laboratory-development multigene pharmacogenetic assay

OBJECTIVE

The implementation of pharmacogenetics (PGx) in clinical practice is an essential tool for personalized medicine. However, clinical laboratories must validate their procedures before being used to perform PGx studies in patients, in order to confirm that they are adequate for the intended purposes.

METHODS

We designed a validation process for our in-house pharmacogenetic PCR-based method assay.

RESULTS

The concordance to reference, repeatability and reproducibility was 100%. Sensitivity and specificity were 100% for the detection of variant diplotypes in CYP2C9, CYP3A5, TPMT, DPYD and UGT1A1 genes. The sensitivity was lower in the detection of CYP2C19 variants due to a limitation in the design that prevents the detection of CYP2C19 *2/*10 diplotype.

CONCLUSIONS

The success of implementing clinical pharmacogenetic testing into routine clinical practice is dependent on the precision of genotyping. Limitations must be bearing in mind to guarantee the quality of PGx assays in clinical laboratory practice. We provided objective evidence that the necessary requirements in our laboratory-development assay were fulfilled.

A Decade of Pharmacogenetic Studies in Jordan: A Systemic Review

The aim of this study was to perform a systematic overview of the pharmacogenetic studies conducted in Jordan. A structured search of Medline was conducted for articles over the last decade (January 2010-July 2020). Studies were classified by design, sample size, drug-gene combination, and the significance of the results. Thirty-two studies met the criteria for review. Most pharmacogenomic studies had a case-only design (n = 23). Only five studies included >500 participants. The total number of genetic variants in all studies was one hundred fifteen, which were found in forty genes, including dynamic (n = 27), and kinetic (n = 9) genes. The most commonly studied drugs were within the hematology and cardiology therapeutic areas and included statins, warfarin, aspirin, and clopidogrel. Most studies (n = 18) reported results with mixed p values [<0.05 and >0.05]. Pharmacogenomic research in Jordan is still in its infancy and is limited mainly to replication attempts. The need for standardization is imperative, especially in developing countries with scarce funding resources.

Pharmacogenomics: A road ahead for precision medicine in psychiatry

Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic ("what the body does to a drug") and pharmacodynamic ("what the drug does to the body") effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.

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

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

The Gene-Drug Duality: Exploring the Pharmacogenomics of Indigenous Populations

While pharmacogenomic studies have facilitated the rapid expansion of personalized medicine, the benefits of these findings have not been evenly distributed. Genomic datasets pertaining to Indigenous populations are sorely lacking, leaving members of these communities at a higher risk of adverse drug reactions (ADRs), and associated negative outcomes. Australia has one of the largest Indigenous populations in the world. Pharmacogenomic studies of these diverse Indigenous Australian populations have been hampered by a paucity of data. In this article, we discuss the history of pharmacogenomics and highlight the inequalities that must be addressed to ensure equal access to pharmacogenomic-based healthcare. We also review efforts to conduct the pharmacogenomic profiling of chronic diseases among Australian Indigenous populations and survey the impact of the lack of drug safety-related information on potential ADRs among individuals in these communities.

PharmVar GeneFocus: CYP2C9

The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C9 gene. Genetic variation within the CYP2C9 gene locus impacts the metabolism or bioactivation of many clinically important drugs, including nonsteroidal anti-inflammatory drugs, phenytoin, antidiabetic agents, and angiotensin receptor blockers. Variable CYP2C9 activity is of particular importance regarding efficacy and safety of warfarin and siponimod as indicated in their package inserts. This GeneFocus provides a comprehensive overview and summary of CYP2C9 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase and the Clinical Pharmacogenetics Implementation Consortium.

Applicability of ancestral genotyping in pharmacogenomic research with hormonal contraception

To compare etonogestrel pharmacokinetic and pharmacodynamic outcomes by both self-reported race/ethnicity and genetically determined ancestry among contraceptive implant users. We conducted a secondary analysis of our parent pharmacogenomic study of 350 implant users. We genotyped these reproductive-aged (18-45 years) women for 88 ancestry-informative single nucleotide polymorphisms. We then assigned each participant a proportion value for African (AFR), European (EUR), and Indigenous American (AMR) ancestry based on reference population data. We correlated genetic ancestry with self-reported race/ethnicity and utilized genetic ancestry proportion values as variables for previously performed association analyses with serum etonogestrel concentrations and progestin-related side effects (e.g., bothersome bleeding and subjective weight gain). We successfully estimated genetically determined ancestry for 332 participants. EUR, AFR, and AMR ancestry were each highly correlated with self-reported White/non-Hispanic race (r = 0.64, p = 4.14 × 10-40 ), Black/African American race (r = 0.88, p = 1.36 × 10-107 ), and Hispanic/Latina ethnicity (r = 0.68, p = 4.03 × 10-47 ), respectively. Neither genetically determined ancestry nor self-reported race/ethnicity were significantly associated with serum etonogestrel concentrations. AFR ancestry and self-reported Black race had similar associations with reporting monthly periods (odds ratio [OR] 2.18, p = 0.09 vs. OR 2.22, p = 0.02) and having received treatment for bothersome bleeding (OR 5.19, p = 0.005 vs. OR 4.73, p = 2.0 × 10-4 ). In multivariable logistic regression for subjective weight gain, AMR ancestry dropped out of the model in preference for self-reported Hispanic/Latina ethnicity. We found no new associations between genetically determined ancestry and contraceptive implant pharmacodynamics/pharmacokinetics. Self-reported race/ethnicity were strong surrogates for genetically determined ancestry among this population of contraceptive implant users. Our data suggest that self-reported race/ethnicity, capturing societal and cultural aspects, remain important to the investigation of progestin-related side effects.

A GRIN3A polymorphism may be associated with glucocorticoid-induced symptomatic osteonecrosis in children with acute lymphoblastic leukemia

Aim: To evaluate the association between candidate genetic polymorphisms and glucocorticoid-induced osteonecrosis in Arab children treated for acute lymphoblastic leukemia. Methods: A total of 189 children treated for acute lymphoblastic leukemia were genotyped for four SNPs with allele discrimination assays. The incidence and timing of radiologically confirmed symptomatic grade 4 osteonecrosis were classified based on the Ponte di Legno toxicity working group consensus definition. Results: Thirteen children developed grade 4 osteonecrosis (6.8%), of whom 12 received the intermediate/high-risk treatment protocol. GRIN3A variant allele carriers had to stop dexamethasone therapy earlier resulting in significantly shorter duration of dexamethasone treatment (mean [95% CI]: 75.17 [64.28-86.06] vs 85.90 [81.22-90.58] weeks; p = 0.054) and lower cumulative dose (mean [95% CI]: 1118.11 [954.94-1281.29] vs 1341.14 [1264.17-1418.11] mg/m^2; p = 0.011). Conclusion: This is the first pharmacogenomics evaluation of the association between GRIN3A variants and glucocorticoid-induced osteonecrosis in Arab children.

Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision

Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.

Genetic Polymorphisms Associated With the Pharmacokinetics, Pharmacodynamics and Adverse Effects of Olanzapine, Aripiprazole and Risperidone

Olanzapine, aripiprazole and risperidone are atypical antipsychotics or neuroleptics widely used for schizophrenia treatment. They induce various adverse drug reactions depending on their mechanisms of action: metabolic effects, such as weight gain and alterations of glucose and lipid metabolism; hyperprolactinemia and extrapyramidal effects, such as tremor, akathisia, dystonia, anxiety and distress. In this review, we listed polymorphisms associated with individual response variability to olanzapine, aripiprazole and risperidone. Olanzapine is mainly metabolized by cytochrome P450 enzymes, CYP1A2 and CYP2D6, whereas aripiprazole and risperidone metabolism is mainly mediated by CYP2D6 and CYP3A4. Polymorphisms in these genes and other enzymes and transporters, such as enzymes from the uridine 5'-diphospho-glucuronosyltransferase (UGT) family and ATP-binding cassette sub-family B member 1 (ABCB1), are associated to differences in pharmacokinetics. The three antipsychotics act on dopamine and serotonin receptors, among others, and several studies found associations between polymorphisms in these genes and variations in the incidence of adverse effects and in the response to the drug. Since olanzapine is metabolized by CYP1A2, a lower starting dose should be considered in patients treated with fluvoxamine or other CYP1A2 inhibitors. Regarding aripiprazole, a reduced dose should be administered in CYP2D6 poor metabolizers (PMs). Additionally, a reduction to a quarter of the normal dose is recommended if the patient is treated with concomitant CYP3A4 inhibitors. Risperidone dosage should be reduced for CYP2D6 PMs and titrated for CYPD6 ultrarapid metabolizers (UMs). Moreover, risperidone dose should be evaluated when a CYP2D6, CYP3A4 or ABCB1 inhibitor is administered concomitantly.

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

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

Pharmacogenomics for Drug Dosing in Children: Current Use, Knowledge, and Gaps

Pharmacogenomics research ranges from the discovery of genetic factors to explain interpatient variability in drug exposure and response to clinical implementation of this knowledge to improve pharmacotherapy. Medications with actionable pharmacogenomic associations are frequently used in children, and therefore pharmacogenomics-guided precision medicine is readily applicable to the pediatric population. Although heritable genetics are considered immutable, the impact of genetic variation in pharmacogenes is modified by other factors such as age-dependent changes in gene expression. Early evidence has emerged indicating that the interaction between ontogeny and pharmacogenomics determines whether or how genetics-based dosing algorithms should be adjusted in children versus adults. However, there is still a paucity of data describing pharmacogenomic associations in patient populations across the life span. Future research is much needed to evaluate the impact of pharmacogenomics on drug dosing specific to the pediatric population, along with consideration of other developmental and physiological factors uniquely related to drug disposition in this population.

Recommendations for Clinical CYP2D6 Genotyping Allele Selection: A Joint Consensus Recommendation of the Association for Molecular Pathology, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, and the European Society for Pharmacogenomics and Personalized Therapy

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing, and to determine a minimal set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations on a minimal panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories in designing assays for PGx testing. When developing these recommendations, the Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations with regard to PGx testing. The ultimate goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document is focused on clinical CYP2D6 PGx testing that may be applied to all cytochrome P450 2D6-metabolized medications. These recommendations are not meant to be interpreted as prescriptive but to provide a reference guide for clinical laboratories that may be either implementing PGx testing or reviewing and updating their existing platform.

Moving Pharmacogenetics Into Practice: It's All About the Evidence!

The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.

Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting

Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug–gene pairs and drug–drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug–gene and drug–drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.

Pharmacogenetic Associations Between Atazanavir/UGT1A1*28 and Efavirenz/rs3745274 (CYP2B6) Account for Specific Adverse Reactions in Chilean Patients Undergoing Antiretroviral Therapy

Background: Efavirenz (EFV), a non-nucleoside reverse transcriptase inhibitor, and atazanavir (ATV), a protease inhibitor, are drugs widely used in antiretroviral therapy (ART) for people living with HIV. These drugs have shown high interindividual variability in adverse drug reactions (ADRs). UGT1A1*28 and CYP2B6 c.516G>T have been proposed to be related with higher toxicity by ATV and EFV, respectively. Objective: To study the association between genetic polymorphisms and ADRs related to EFV or ATV in patients living with HIV treated at a public hospital in Chile. Methods: Epidemiologic, case-control, retrospective, observational study in 67 adult patients under EFV or ATV treatment was conducted, in the San Juan de Dios Hospital. Data were obtained from patients' medical records. Genotype analyses were performed using rtPCR for rs887829 (indirect identification of UGT1A1*28 allele) and rs3745274 (CYP2B6 c.516G>T), with TaqMan® probes. The association analyses were performed with univariate logistic regression between genetic variants using three inheritance models (codominant, recessive, and dominant). Results: In ATV-treated patients, hyperbilirubinemia (total bilirubin >1.2 mg/dl) had the main incidence (61.11%), and moderate and severe hyperbilirubinemia (total bilirubin >1.9 mg/dl) were statistically associated with UGT1A1*28 in recessive and codominant inheritance models (OR = 16.33, p = 0.028 and OR = 10.82, p = 0.036, respectively). On the other hand, in EFV-treated patients adverse reactions associated with CNS toxicity reached 34.21%. In this respect, nightmares showed significant association with CYP2B6 c.516G>T, in codominant and recessive inheritance models (OR = 12.00, p = 0.031 and OR = 7.14, p = 0.042, respectively). Grouped CNS ADRs (nightmares, insomnia, anxiety, and suicide attempt) also showed a statistically significant association with CYP2B6 c.516G > T in the codominant and recessive models (OR = 30.00, p = 0.011 and OR = 14.99, p = 0.021, respectively). Conclusion: Our findings suggest that after treatment with ATV or EFV, UGT1A1*28 and CYP2B6 c.516G>T influence the appearance of moderate-to-severe hyperbilirubinemia and CNS toxicity, respectively. However, larger prospective studies will be necessary to validate these associations in our population. Without a doubt, improving adherence in patients living with HIV is a critical issue to the success of therapy. Hence, validating and applying international pharmacogenetic recommendations in Latin American countries would improve the precision of ART: a fundamental aspect to achieve the 95-95-95 treatment target proposed by UNAIDS.

Patients with geographic barriers to health care access are prescribed a higher proportion of drugs with pharmacogenetic testing guidelines

Pharmacogenetic (PGx) testing may be particularly beneficial in medically underserved populations by reducing the number of appointments required to optimize drug therapy and increasing the effectiveness of less expensive off-patent drugs. The objective of this study was to identify patient populations with poor health care access and assess prescribing trends for drugs with published PGx testing guidelines. We used electronic health record data from 67,753 University of Florida Health patients, geographic access scores calculated via the 2-step floating catchment area method, and a composite measure of socioeconomic status. Comparing the poorest (Q4) and greatest (Q1) access score quartiles, poor geographic access was significantly associated with fewer prescriber encounters (incidence rate ratio [IRR] 0.88, 95% confidence interval [CI] 0.86-0.91), fewer total unique drugs (IRR 0.92, 95% CI 0.9-0.95), and fewer PGx guideline drugs (IRR 0.94, 95% CI 0.9-0.99). After correcting for number of unique drugs, patients in low-access areas were prescribed a greater proportion of PGx guideline drugs (IRR 1.08, 95% CI 1.04-1.13). We detected significant interactions between Black race and access score. Compared to Q1, Black patients with Q4 access scores were disproportionately affected and had fewer encounters (IRR 0.76, 95% CI 0.7-0.82) and a higher proportion of PGx drugs (IRR 1.26, 95% CI 1.13-1.41), creating further disparity. Overall, these results suggest that improved geographic access to PGx testing may allow prescribers to make more efficient use of limited opportunities to optimize therapy for drugs with PGx testing guidelines.

Different Pharmacokinetics of Tramadol, O-Demethyltramadol and N-Demethyltramadol in Postoperative Surgical Patients From Those Observed in Medical Patients

Background: Most studies examining tramadol metabolism have been carried out in non-surgical patients and with oral tramadol. The aim of this study was 1) to measure concentrations of tramadol, O-demethyltramadol (ODT), and N-demethyltramadol (NDT) in the surgical patients admitted to the intensive care unit (ICU) within the first 24 postoperative hours after intravenous application of tramadol, and 2) to examine the effect of systemic inflammation on tramadol metabolism and postoperative pain. Methods: A prospective observational study was carried out in the surgical ICU in the tertiary hospital. In the group of 47 subsequent patients undergoing major abdominal surgery, pre-operative blood samples were taken for CYP2D6 polymorphism analysis. Systemic inflammation was assessed based on laboratory and clinical indicators. All patients received 100 mg of tramadol intravenously every 6 h during the first postoperative day. Postoperative pain was assessed before and 30 min after tramadol injections. Tramadol, ODT, and NDT concentrations were determined by high-performance liquid chromatography. Results: CYP2D6 analysis revealed 2 poor (PM), 22 intermediate (IM), 22 extensive (EM), and 1 ultrafast metabolizer. After a dose of 100 mg of tramadol, t1/2 of 4.8 (3.2-7.6) h was observed. There were no differences in tramadol concentration among metabolic phenotypes. The area under the concentration-time curve at the first dose interval (AUC1-6) of tramadol was 1,200 (917.9-1944.4) μg ×h ×L-1. NDT concentrations in UM were below the limit of quantification until the second dose of tramadol was administrated, while PM had higher NDT concentrations compared to EM and IM. ODT concentrations were higher in EM, compared to IM and PM. ODT AUC1-6 was 229.6 (137.7-326.2) μg ×h ×L-1 and 95.5 (49.1-204.3) μg ×h ×L-1 in EM and IM, respectively (p = 0.004). Preoperative cholinesterase activity (ChE) of ≤4244 U L-1 was a cut-off value for a prediction of systemic inflammation in an early postoperative period. NDT AUC1-6 were significantly higher in patients with low ChE compared with normal ChE patients (p = 0.006). Pain measurements have confirmed that sufficient pain control was achieved in all patients after the second tramadol dose, except in the PM. Conclusions: CYP2D6 polymorphism is a major factor in O-demethylation, while systemic inflammation accompanied by low ChE has an important role in the N-demethylation of tramadol in postoperative patients. Concentrations of tramadol, ODT, and NDT are lower in surgical patients than previously reported in non-surgical patients. Clinical Trial Registration: ClinicalTrials.gov, NCT04004481.

Prototype Development and Usability Evaluation of a Clinical Decision Support Tool for Pharmacogenomic Pharmacy in Practice

Pharmacogenetics, a subset of precision medicine, provides a way to individualize drug dosages and provide tailored drug therapy to patients. This revolution in prescribing techniques has resulted in a knowledge deficit for many healthcare providers on the proper way to use pharmacogenetics in practice. This research study explored the potential adoption of clinical decision support system mobile apps by clinicians through investigating the initial usability of the PGx prototype application in an effort to address the lack of such tools used in practice. The study method included usage of a clinical decision support system programmed within our pharmacogenomics drug dosage application (called PGx) in a simulated environment. Study participants completed the System Usability Scale survey to report on the perceived usefulness and ease of use of the mobile app. The PGx app has a higher perceived usability than 85% of all products tested, considered very good usability for a product. This general usability rating indicates that the nurse practitioner students find the application to be a clinical decision support system that would be helpful to use in practice.

UGT1A1 Guided Cancer Therapy: Review of the Evidence and Considerations for Clinical Implementation

Multi-gene assays often include UGT1A1 and, in certain instances, may report associated toxicity risks for irinotecan, belinostat, pazopanib, and nilotinib. However, guidance for incorporating UGT1A1 results into therapeutic decision-making is mostly lacking for these anticancer drugs. We summarized meta-analyses, genome-wide association studies, clinical trials, drug labels, and guidelines relating to the impact of UGT1A1 polymorphisms on irinotecan, belinostat, pazopanib, or nilotinib toxicities. For irinotecan, UGT1A1*28 was significantly associated with neutropenia and diarrhea, particularly with doses ≥ 180 mg/m2, supporting the use of UGT1A1 to guide irinotecan prescribing. The drug label for belinostat recommends a reduced starting dose of 750 mg/m2 for UGT1A1*28 homozygotes, though published studies supporting this recommendation are sparse. There was a correlation between UGT1A1 polymorphisms and pazopanib-induced hepatotoxicity, though further studies are needed to elucidate the role of UGT1A1-guided pazopanib dose adjustments. Limited studies have investigated the association between UGT1A1 polymorphisms and nilotinib-induced hepatotoxicity, with data currently insufficient for UGT1A1-guided nilotinib dose adjustments.

A retrospective analysis of actionable pharmacogenetic/genomic biomarker language in FDA labels

The primary goal of precision medicine is to maximize the benefit‐risk relationships for individual patients by delivering the right drug to the right patients at the right dose. To achieve this goal, it has become increasingly important to assess gene‐drug interactions (GDIs) in clinical settings. The US Food and Drug Administration (FDA) periodically updates the table of pharmacogenetic/genomic (PGx) biomarkers in drug labeling on their website. As described herein, an effort was made to categorize various PGx biomarkers covered by the FDA‐PGx table into certain groups. There were 2 major groups, oncology molecular targets (OMT) and drug‐metabolizing enzymes and transporters (DMETs), which constitute ~70% of all biomarkers (~33% and ~35%, respectively). These biomarkers were further classified whether their labeling languages could be actionable in clinical practice. For OMT biomarkers, ~70% of biomarkers are considered actionable in clinical practice as they are critical for the selection of appropriate drugs to individual patients. In contrast, ~30% of DMET biomarkers are considered actionable for the dose adjustments or alternative therapies in specific populations, such as CYP2C19 and CYP2D6 poor metabolizers. In addition, the GDI results related to some of the other OMT and DMET biomarkers are considered to provide valuable information to clinicians. However, clinical GDI results on the other DMET biomarkers can possibly be used more effectively for dose recommendation. As the labels of some drugs already recommend the precise doses in specific populations, it will be desirable to have clear language for dose recommendation of other (or new) drugs if appropriate.

Sequence2Script: A Web-Based Tool for Translation of Pharmacogenetic Data Into Evidence-Based Prescribing Recommendations

Pharmacogenomic (PGx) testing has emerged as an effective strategy for informing drug selection and dosing. This has led to an increase in the use of PGx testing in the clinic and has catalyzed the emergence of a burgeoning commercial PGx testing industry. However, not all PGx tests are equivalent in their approach to translating testing results into prescribing recommendations, due to an absence of regulatory standards. As such, those generating and using PGx data require tools for ensuring the prescribing recommendations they are provided align with current peer-reviewed PGx-based prescribing guidelines developed by expert groups or approved product labels. Herein, we present Sequence2Script (sequence2script.com), a simple, free, and transparent web-based tool to assist in the efficient translation of PGx testing results into evidence-based prescribing recommendations. The tool was designed with a wide-range of user groups (e.g., healthcare providers, laboratory staff, researchers) in mind. The tool supports 97 gene-drug pairs with evidence-based prescribing guidelines, allows users to adjust recommendations for concomitant inhibitors and inducers, and generates a clinical report summarizing the patient's genotype, inferred phenotype, phenoconverted phenotype (if applicable), and corresponding prescribing recommendations. In this paper, we describe each of the tool's features, provide use case examples, and discuss limitations of and future development plans for the tool. Although we recognize that Sequecnce2Script may not meet the needs of every user, the hope is that this novel tool will facilitate more standardized use of PGx testing results and reduce barriers to implementing these results into practice.

Functional Assessment of 12 Rare Allelic CYP2C9 Variants Identified in a Population of 4773 Japanese Individuals

Cytochrome P450 2C9 (CYP2C9) is an important drug-metabolizing enzyme that contributes to the metabolism of approximately 15% of clinically used drugs, including warfarin, which is known for its narrow therapeutic window. Interindividual differences in CYP2C9 enzymatic activity caused by CYP2C9 genetic polymorphisms lead to inconsistent treatment responses in patients. Thus, in this study, we characterized the functional differences in CYP2C9 wild-type (CYP2C9.1), CYP2C9.2, CYP2C9.3, and 12 rare novel variants identified in 4773 Japanese individuals. These CYP2C9 variants were heterologously expressed in 293FT cells, and the kinetic parameters (K_m, k_cat, V_max, catalytic efficiency, and CL_int) of (S)-warfarin 7-hydroxylation and tolbutamide 4-hydroxylation were estimated. From this analysis, almost all novel CYP2C9 variants showed significantly reduced or null enzymatic activity compared with that of the CYP2C9 wild-type. A strong correlation was found in catalytic efficiencies between (S)-warfarin 7-hydroxylation and tolbutamide 4-hydroxylation among all studied CYP2C9 variants. The causes of the observed perturbation in enzyme activity were evaluated by three-dimensional structural modeling. Our findings could clarify a part of discrepancies among genotype–phenotype associations based on the novel CYP2C9 rare allelic variants and could, therefore, improve personalized medicine, including the selection of the appropriate warfarin dose.

PharmVar GeneFocus: CYP2C19

The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C19 gene. CYP2C19 genetic variation impacts the metabolism of many drugs and has been associated with both efficacy and safety issues for several commonly prescribed medications. This GeneFocus provides a comprehensive overview and summary of CYP2C19 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Pharmacogenomics cascade testing (PhaCT): a novel approach for preemptive pharmacogenomics testing to optimize medication therapy

The implementation of pharmacogenomics (PGx) has come a long way since the dawn of utilizing pharmacogenomic data in clinical patient care. However, the potential benefits of sharing PGx results have yet to be explored. In this paper, we explore the willingness of patients to share PGx results, as well as the inclusion of family medication history in identifying potential family members for pharmacogenomics cascade testing (PhaCT). The genetic similarities in families allow for identifying potential gene variants prior to official preemptive testing. Once a candidate patient is determined, PhaCT can be initiated. PhaCT recognizes that further cascade testing throughout a family can serve to improve precision medicine. In order to make PhaCT feasible, we propose a novel shareable HIPAA-compliant informatics platform that will enable patients to manage not only their own test results and medications but also those of their family members. The informatics platform will be an external genomics system with capabilities to integrate with patients' electronic health records. Patients will be given the tools to provide information to and work with clinicians in identifying family members for PhaCT through this platform. Offering patients the tools to share PGx results with their family members for preemptive testing could be the key to empowering patients. Clinicians can utilize PhaCT to potentially improve medication adherence, which may consequently help to distribute the burden of health management between patients, family members, providers, and payers.

Pharmacogenetics Guidelines: Overview and Comparison of the DPWG, CPIC, CPNDS, and RNPGx Guidelines

Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

Evaluation of clinical impact of pharmacogenomics knowledge involved in CPIC guidelines on Chinese pediatric patients

Aim: To evaluate the clinical benefits of implementing pharmacogenomics testing for Chinese pediatric patients. Materials & methods : Based on the drug-gene interactions involved in the Clinical Pharmacogenetics Implementation Consortium guidelines, whole-genome sequencing data from the Chinese Academy of Sciences Precision Medicine Initiative project and the medication data of pediatric patients from a children's hospital, the prevalence of the Chinese population with actionable pharmacogenomic variants was calculated, the prescribing pattern for pediatric patients was analyzed. Results: 37.0% of the drugs involved in the Clinical Pharmacogenetics Implementation Consortium guidelines were used by Chinese pediatric patients, 8.91% inpatients and 0.89% outpatients received at least one pharmacogenomics medication, 1.24% (4803) inpatients and 0.16% (2940) outpatients were estimated to be at high risk of pharmacogenomic-related adverse therapeutic outcomes. Conclusion: Implementing pharmacogenomics testing can improve therapeutic outcomes for many Chinese pediatric patients.

Considerations When Applying Pharmacogenomics to Your Practice

Many practitioners who have not had pharmacogenomic education are required to apply pharmacogenomics to their practices. Although many aspects of pharmacogenomics are similar to traditional concepts of drug-drug interactions, there are some differences. We searched PubMed with the search terms pharmacogenomics and pharmacogenetics (January 1, 2005, through December 31, 2019) and selected articles that supported the application of pharmacogenomics to practice. For inclusion, we gave preference to national and international consortium guidelines for implementation of pharmacogenomics. We discuss special considerations important in the application of pharmacogenomics to assist clinicians with ordering, interpreting, and applying pharmacogenomics in their practices.

Pharmacogenetic Testing: A Tool for Personalized Drug Therapy Optimization

Pharmacogenomics is a study of how the genome background is associated with drug resistance and how therapy strategy can be modified for a certain person to achieve benefit. The pharmacogenomics (PGx) testing becomes of great opportunity for physicians to make the proper decision regarding each non-trivial patient that does not respond to therapy. Although pharmacogenomics has become of growing interest to the healthcare market during the past five to ten years the exact mechanisms linking the genetic polymorphisms and observable responses to drug therapy are not always clear. Therefore, the success of PGx testing depends on the physician's ability to understand the obtained results in a standardized way for each particular patient. The review aims to lead the reader through the general conception of PGx and related issues of PGx testing efficiency, personal data security, and health safety at a current clinical level.

Pharmacogenomic information from CPIC and DPWG guidelines and its application on drug labels

There are several hurdles to overcome before implementing pharmacogenomics (PGx) in precision medicine. One of the hurdles is unawareness of PGx by clinicians due to insufficient pharmacogenomic information on drug labels. Therefore, it might be important to implement PGx that reflects pharmacogenomic information on drug labels, standard of prescription for clinicians. This study aimed to evaluate the level at which PGx was being used in clinical practice by comparing the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines and drug labels of the US Food and Drug Administration (FDA) and the Korea Ministry of Food and Drug Safety (MFDS). Two PGx guidelines and drugs labels were scrutinized, and the concordance of the pharmacogenomic information between guidelines and drug labels was confirmed. The concordance of the label between FDA and MFDS was analyzed. In FDA labels, the number of concordant drug with guidelines was 24, while 13 drugs were concordant with MFDS labels. The number of drugs categorized as contraindication, change dose, and biomarker testing required was 7, 12 and 12 for the FDA and 8, 5 and 4 for the MFDS, respectively. The pharmacogenomic information of 9 drugs approved by both FDA and MFDS was identical. In conclusion, pharmacogenomic information on clinical implementation guidelines was limited on both FDA and MFDS labels because of various reasons including the characteristics of the guidelines and the drug labels. Therefore, more effort from pharmaceutical companies, academia and regulatory affairs needs to be made to implement pharmacogenomic information on drug labels.

How Can Drug Metabolism and Transporter Genetics Inform Psychotropic Prescribing?

Many genetic variants in drug metabolizing enzymes and transporters have been shown to be relevant for treating psychiatric disorders. Associations are strong enough to feature on drug labels and for prescribing guidelines based on such data. A range of commercial tests are available; however, there is variability in included genetic variants, methodology, and interpretation. We herein provide relevant background for understanding clinical associations with specific variants, other factors that are relevant to consider when interpreting such data (such as age, gender, drug-drug interactions), and summarize the data relevant to clinical utility of pharmacogenetic testing in psychiatry and the available prescribing guidelines. We also highlight areas for future research focus in this field.