ABSTRACT
Pharmacogenomics (PGx) investigates the influence of genetics on drug responses, enabling tailored treatments for personalized healthcare. This study assessed the accuracy of genotyping six genes using whole genome sequencing with four different computational tools and various sequencing depths. The effects of using different reference genomes (GRCh38 and GRCh37) and sequence aligners (BWA-MEM and Bowtie2) were also explored. The results showed generally minor variations in tool performance across most genes; however, more notable discrepancies were observed in the analysis of the complex CYP2D6 gene. Cyrius, a CYP2D6-specific tool, demonstrated the most robust performance, achieving the highest concordance rates for CYP2D6 in all instances, comparable to the consensus approach in most cases. There were rather small differences between the samples with 20× coverage depth and those with higher depth, but the decreased performance was more evident at lower depths, particularly at 5×. Additionally, variations in CYP2D6 results were observed when samples were aligned to different reference genomes using the same method, or to the same genome using different aligners, which led to reporting incorrect rare star alleles in several cases. These findings inform the selection of optimal PGx tools and methodologies as well as suggest that employing a consensus approach with two or more tools might be preferable for certain genes and tool combinations, especially at lower sequencing depths, to ensure accurate results. Additionally, we show how the upstream alignment can affect the performance of tools, an important factor to take into account.
Subject(s)
Benchmarking , Cytochrome P-450 CYP2D6 , Pharmacogenetics , Humans , Cytochrome P-450 CYP2D6/genetics , Pharmacogenetics/standards , Pharmacogenetics/methods , Cytochrome P-450 CYP2C19/genetics , Whole Genome Sequencing/standards , Whole Genome Sequencing/methods , Genotyping Techniques/methods , Genotype , Cytochrome P-450 CYP2C9/genetics , Cytochrome P-450 CYP2A6/genetics , Pharmacogenomic Testing/standards , Pharmacogenomic Testing/methods , High-Throughput Nucleotide Sequencing/standards , Vitamin K Epoxide ReductasesABSTRACT
PURPOSE: Pharmacogenetic testing can identify patients who may benefit from personalized drug treatment. However, clinical uptake of pharmacogenetic testing has been limited. Clinical practice guidelines recommend biomarker tests that the guideline authors deem to have demonstrated clinical utility, meaning that testing improves treatment outcomes. The objective of this narrative review is to describe the current status of pharmacogenetic testing recommendations within clinical practice guidelines in the US. SUMMARY: Guidelines were reviewed for pharmacogenetic testing recommendations for 21 gene-drug pairs that have well-established drug response associations and all of which are categorized as clinically actionable by the Clinical Pharmacogenetics Implementation Consortium. The degree of consistency within and between organizations in pharmacogenetic testing recommendations was assessed. Relatively few clinical practice guidelines that provide a pharmacogenetic testing recommendation were identified. Testing recommendations for HLA-B*57:01 before initiation of abacavir and G6PD before initiation of rasburicase, both of which are included in drug labeling, were mostly consistent across guidelines. Gene-drug pairs with at least one clinical practice guideline recommending testing or stating that testing could be considered included CYP2C19-clopidogrel, CYP2D6-codeine, CYP2D6-tramadol, CYP2B6-efavirenz, TPMT-thiopurines, and NUDT15-thiopurines. Testing recommendations for the same gene-drug pair were often inconsistent between organizations and sometimes inconsistent between different guidelines from the same organization. CONCLUSION: A standardized approach to evaluating the evidence of clinical utility for pharmacogenetic testing may increase the inclusion and consistency of pharmacogenetic testing recommendations in clinical practice guidelines, which could benefit patients and society by increasing clinical use of pharmacogenetic testing.
Subject(s)
Pharmacogenomic Testing , Practice Guidelines as Topic , Humans , Pharmacogenomic Testing/methods , Pharmacogenomic Testing/standards , United States , Pharmacogenetics/methods , Pharmacogenetics/standards , Precision Medicine/methods , Precision Medicine/standardsABSTRACT
Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug-response analysis such as tissue distribution of dose-response metrics and biomarker analysis; and (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug-response phenotypes of cancer models.
Subject(s)
Databases, Genetic , Pharmacogenetics/standards , Pharmacogenomic Testing/methods , Software , Genomics/methods , HumansABSTRACT
Opioid misuse and mismanagement has been a public health crisis for several years. Pharmacogenomics (PGx) has been proposed as another tool to enhance opioid selection and optimization, with recent studies demonstrating successful implementation and outcomes. However, broad engagement with PGx for opioid management is presently limited. The purpose of this article is to highlight a series of barriers to PGx implementation within the specific context of opioid management. Areas of advancement needed for more robust pharmacogenomic engagement with opioids will be discussed, including clinical and economic research needs, education and training needs, policy and public health considerations, as well as legal and ethical issues. Continuing efforts to address these issues may help to further operationalize PGx toward improving opioid use.
Subject(s)
Analgesics, Opioid/administration & dosage , Opioid-Related Disorders/prevention & control , Pain Management/standards , Pharmacogenetics/standards , Practice Guidelines as Topic/standards , Public Health Practice/standards , Analgesics, Opioid/adverse effects , Humans , Opioid-Related Disorders/epidemiology , Pain/drug therapy , Pain/epidemiology , Pain Management/ethics , Pharmacogenetics/methods , Public Health Practice/ethics , Public Health Practice/legislation & jurisprudenceABSTRACT
The application of pharmacogenomics could meaningfully contribute toward medicines optimization within primary care. This review identified 13 studies describing eight implementation models utilizing a multi-gene pharmacogenomic panel within a primary care or community setting. These were small feasibility studies (n <200). They demonstrated importance and feasibility of pre-test counseling, the role of the pharmacist, data integration into the electronic medical record and point-of-care clinical decision support systems (CDSS). Findings were considered alongside existing primary care prescribing practices and implementation frameworks to demonstrate how issues may be addressed by existing nationalized healthcare and primary care infrastructure. Development of point-of-care CDSS should be prioritized; establishing clinical leadership, education programs, defining practitioner roles and responsibilities and addressing commissioning issues will also be crucial.
Subject(s)
Decision Support Systems, Clinical/trends , Drug Prescriptions , Pharmacogenomic Testing/methods , Primary Health Care/methods , Decision Support Systems, Clinical/standards , Drug Prescriptions/standards , Humans , Pharmacists/standards , Pharmacists/trends , Pharmacogenetics/methods , Pharmacogenetics/standards , Pharmacogenetics/trends , Pharmacogenomic Testing/standards , Pharmacogenomic Testing/trends , Primary Health Care/standards , Primary Health Care/trendsABSTRACT
Clinical annotations are one of the most popular resources available on the Pharmacogenomics Knowledgebase (PharmGKB). Each clinical annotation summarizes the association between variant-drug pairs, shows relevant findings from the curated literature, and is assigned a level of evidence (LOE) to indicate the strength of support for that association. Evidence from the pharmacogenomic literature is curated into PharmGKB as variant annotations, which can be used to create new clinical annotations or added to existing clinical annotations. This means that the same clinical annotation can be worked on by multiple curators over time. As more evidence is curated into PharmGKB, the task of maintaining consistency when assessing all the available evidence and assigning an LOE becomes increasingly difficult. To remedy this, a scoring system has been developed to automate LOE assignment to clinical annotations. Variant annotations are scored according to certain attributes, including study size, reported P value, and whether the variant annotation supports or fails to find an association. Clinical guidelines or US Food and Drug Administration (FDA)-approved drug labels which give variant-specific prescribing guidance are also scored. The scores of all annotations attached to a clinical annotation are summed together to give a total score for the clinical annotation, which is used to calculate an LOE. Overall, the system increases transparency, consistency, and reproducibility in LOE assignment to clinical annotations. In combination with increased standardization of how clinical annotations are written, use of this scoring system helps to ensure that PharmGKB clinical annotations continue to be a robust source of pharmacogenomic information.
Subject(s)
Pharmacogenetics/standards , Precision Medicine/standards , Databases, Genetic/standards , Drug Labeling/standards , Drug Prescriptions/standards , Humans , Knowledge Bases , Prescription Drugs/standards , Reproducibility of ResultsSubject(s)
Biomedical Research/trends , Clinical Pharmacy Information Systems/trends , Health Care Sector/trends , Pharmacogenetics/trends , Precision Medicine/trends , Biomedical Research/standards , Clinical Pharmacy Information Systems/standards , Health Care Sector/standards , Humans , Pharmacogenetics/standards , Precision Medicine/standardsABSTRACT
Given the expansion of genetics in medicine, there is a growing need to develop approaches to engage patients in understanding how genetics affects their health. Various qualitative methods have been applied to gain a deeper understanding of patient perspectives in topics related to genetics. Community dialogues (CD) are a bi-directional research method that invites community members to discuss a pertinent, challenging topic over the course of a multi-week period and the community members openly discuss their positions on the topic. Authors discuss the first application of the CD method to the topic of pharmacogenetics testing. Additional CD are needed to engage diverse participant populations on this topic to improve genetics literacy, enhance physician engagement and drive policy change.
Subject(s)
Health Literacy/ethics , Pharmacogenetics/ethics , Pharmacogenomic Testing/ethics , Precision Medicine/ethics , Bioethical Issues/standards , Focus Groups/standards , Health Literacy/standards , Humans , Pharmacogenetics/standards , Pharmacogenomic Testing/standards , Precision Medicine/standardsABSTRACT
Vanderbilt University Medical Center implemented pharmacogenomics (PGx) testing with the Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT) initiative in 2010. This tutorial reviews the laboratory considerations, technical infrastructure, and programmatic support required to deliver panel-based PGx testing across a large health system with examples and experiences from the first decade of the PREDICT initiative. From the time of inception, automated clinical decision support (CDS) has been a critical capability for delivering PGx results to the point-of-care. Key features of the CDS include human-readable interpretations and clinical guidance that is anticipatory, actionable, and adaptable to changes in the scientific literature. Implementing CDS requires that structured results from the laboratory be encoded in standards-based messages that are securely ingested by electronic health records. Translating results to guidance also requires an informatics infrastructure with multiple components: (1) to manage the interpretation of raw genomic data to "star allele" results to expected phenotype, (2) to define the rules that associate a phenotype with recommended changes to clinical care, and (3) to manage and update the knowledge base. Knowledge base management is key to processing new results with the latest guidelines, and to ensure that historical genomic results can be reinterpreted with revised CDS. We recommend that these components be deployed with institutional authorization, programmatic support, and clinician education to govern the CDS content and policies around delivery.
Subject(s)
Decision Support Systems, Clinical/standards , Pharmacogenetics/methods , Pharmacogenetics/standards , Genomics/standards , Humans , Point-of-Care Systems/standards , Precision Medicine/methods , Precision Medicine/standardsABSTRACT
The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance criteria is an error-prone process. Recently, pharmacogenetic biomarkers entered in prescribing guidelines, giving clinicians the possibility to use this additional tool to guide prescription and improve therapeutic outcomes. This marked an important step towards precision psychiatry, which aim is to integrate biological and environmental information to personalise treatments. Only genetic variants in cytochrome enzymes are endorsed by prescribing guidelines, but in the future polygenic predictors of treatment outcomes may be translated into the clinic. The integration of genetics with other relevant information (e.g., concomitant diseases and treatments, drug plasma levels) could be managed in a standardised way through ad hoc software. The overcoming of the current obstacles (e.g., staff training, genotyping and informatics facilities) can lead to a broad implementation of precision psychiatry and represent a revolution for psychiatric care.Key pointsPrecision psychiatry aims to integrate biological and environmental information to personalise treatments and complement clinical judgementPharmacogenetic biomarkers in cytochrome genes were included in prescribing guidelines and represented an important step towards precision psychiatryTherapeutic drug monitoring is an important and cost-effective tool which should be integrated with genetic testing and clinical evaluation in order to optimise pharmacotherapyOther individual factors relevant to pharmacotherapy response (e.g., individual's symptom profile, concomitant diseases) can be integrated with genetic information through artificial intelligence to provide treatment recommendationsThe creation of pharmacogenetic services within healthcare systems is a challenging and multi-step process, education of health professionals, promotion by institutions and regulatory bodies, economic and ethical barriers are the main issues.
Subject(s)
Antidepressive Agents , Artificial Intelligence , Depressive Disorder/drug therapy , Drug Monitoring , Pharmacogenetics , Precision Medicine , Psychiatry , Artificial Intelligence/standards , Drug Monitoring/methods , Drug Monitoring/standards , Humans , Pharmacogenetics/methods , Pharmacogenetics/standards , Precision Medicine/methods , Precision Medicine/standards , Psychiatry/methods , Psychiatry/standardsABSTRACT
Decades of research have produced extensive evidence of the contribution of genetic factors to the efficacy and toxicity of antipsychotics. Numerous genetic variants in genes controlling drug availability or involved in antipsychotic processes have been linked to treatment variability. The complex mechanism of action and multitarget profile of most antipsychotic drugs hinder the identification of pharmacogenetic markers of clinical value. Nevertheless, the validity of associations between variants in CYP1A2, CYP2D6, CYP2C19, ABCB1, DRD2, DRD3, HTR2A, HTR2C, BDNF, COMT, MC4R genes and antipsychotic response has been confirmed in independent candidate gene studies. Genome wide pharmacogenomic studies have proven the role of the glutamatergic pathway in mediating antipsychotic activity and have reported novel associations with antipsychotic response. However, only a limited number of the findings, mainly functional variants of CYP metabolic enzymes, have been shown to be of clinical utility and translated into useful pharmacogenetic markers. Based on the currently available information, actionable pharmacogenetics should be reduced to antipsychotics' dose adjustment according to the genetically predicted metabolic status (CYPs' profile) of the patient. Growing evidence suggests that such interventions will reduce antipsychotics' side-effects and increase treatment safety. Despite this evidence, the use of pharmacogenetics in psychiatric wards is minimal. Hopefully, further evidence on the clinical and economic benefits, the development of clinical protocols based on pharmacogenetic information, and improved and cheaper genetic testing will increase the implementation of pharmacogenetic guided prescription in clinical settings.
Subject(s)
Antipsychotic Agents/metabolism , Pharmacogenetics , Precision Medicine , Antipsychotic Agents/administration & dosage , Humans , Pharmacogenetics/standards , Precision Medicine/standardsABSTRACT
Pharmacogenomics is rapidly assuming an integral part in modern health care. Still, its broad applicability relies on the feasibility of performing pharmacogenomic testing in all clinical settings, including in remote areas or resource-limited settings with budget restrictions. In this study, we describe the development and feasibility of rapid and reliable pharmacogenomics assays using a portable molecular biology laboratory, namely the 2MoBiL (Mobile Molecular Biology Laboratory). More precisely, we demonstrate that the genotyping of rs4149056, located within SLCO1B1, can be efficiently and reliably performed using the 2MoBiL portable laboratory and conventional benchtop laboratory equipment and a gold standard genotyping method (KASP assay) as directly comparable methodologies. Taking into account the compact size of 2MoBiL, which directly and positively impacts on its portability, and the high accuracy achieved, we conclude that the 2MoBiL-based genotyping method is warranted for further studies in clinical practices at remote areas and resource-limited as well as time-constrained planetary health settings. To contextualize the broader and potential future applications of 2MoBiL, we emphasize that genotyping of a limited set of clinically relevant single-nucleotide polymorphisms is often a common endpoint of genomics and pharmacogenomics discovery and translational research pipeline. Hence, rapid genotyping by 2MoBiL can be an essential catalyst for global implementation of pharmacogenomics and personalized medicine in the clinic. The Clinical Trial Registration number is NCT03093818.
Subject(s)
Laboratories , Mobile Health Units , Molecular Biology/methods , Pharmacogenetics/methods , Pharmacogenomic Testing/methods , Alleles , Genotyping Techniques/methods , Genotyping Techniques/standards , Humans , Molecular Biology/standards , Pharmacogenetics/standards , Pharmacogenomic Testing/standards , Translational Research, Biomedical , WorkflowABSTRACT
BACKGROUND: Large sample sizes are often required to detect statistically significant associations between pharmacogenetic markers and treatment response. Meta-analysis may be performed to synthesize data from several studies, increasing sample size and, consequently, power to detect significant genetic effects. However, performing robust synthesis of data from pharmacogenetic studies is often challenging because of poor reporting of key data in study reports. There is currently no guideline for the reporting of pharmacogenetic studies that has been developed using a widely accepted robust methodology. The objective of this project was to develop the STrengthening the Reporting Of Pharmacogenetic Studies (STROPS) guideline. METHODS AND FINDINGS: We established a preliminary checklist of reporting items to be considered for inclusion in the guideline. We invited representatives of key stakeholder groups to participate in a 2-round Delphi survey. A total of 52 individuals participated in both rounds of the survey, scoring items with regards to their importance for inclusion in the STROPS guideline. We then held a consensus meeting, at which 8 individuals considered the results of the Delphi survey and voted on whether each item ought to be included in the final guideline. The STROPS guideline consists of 54 items and is accompanied by an explanation and elaboration document. The guideline contains items that are particularly important in the field of pharmacogenetics, such as the drug regimen of interest and whether adherence to treatment was accounted for in the conducted analyses. The guideline also requires that outcomes be clearly defined and justified, because in pharmacogenetic studies, there may be a greater number of possible outcomes than in other types of study (for example, disease-gene association studies). A limitation of this project is that our consensus meeting involved a small number of individuals, the majority of whom are based in the United Kingdom. CONCLUSIONS: Our aim is for the STROPS guideline to improve the transparency of reporting of pharmacogenetic studies and also to facilitate the conduct of high-quality systematic reviews and meta-analyses. We encourage authors to adhere to the STROPS guideline when publishing pharmacogenetic studies.
Subject(s)
Pharmacogenetics/methods , Pharmacogenomic Testing/standards , Pharmacogenomic Testing/trends , Adult , Checklist , Consensus , Delphi Technique , Female , Genetic Association Studies , Goals , Humans , Male , Middle Aged , Pharmacogenetics/standards , Politics , Publishing/standards , Research Design/standards , Stakeholder Participation , Surveys and Questionnaires , United KingdomABSTRACT
INTRODUCTION: Pharmacogenetics represents an opportunity in pharmaceutical practice. There are many documentary resources to support the pharmacist's work in this area. OBJECTIVE: To compare the recommendations for carrying out pharmacogenetic tests from a documentary source in three countries: the United States, Canada and United France. METHOD: This is a cross-sectional descriptive study. Based on the recommendations of the Clinical Pharmacogenetics Implementation Consortium type A (the highest threshold justifying the use of a pharmacogenetic test), we identified the drug-gene pairs (23 pairs). The proposed pairs involve a total of 47 separate international nonproprietary names and 18 genes. For each drug-gene pair, we consulted three open access documentary sources (one for each target country), namely the pharmaceutical products database (DPD) for Canada, the product characteristic summary (SPC) for France and the Micromedex® monograph (IBM, Truven Health Analytics, MI, USA) for the United States. The study was conducted in September 2019. RESULTS: About a third of the drug-gene pairs are explicitly mentioned by the gene to be targeted and by the test suggested in the documentary sources consulted. Of the 23 pairs identified by the CPIC, thirteen pairs contain "consistent" recommendations between the three documentary sources. CONCLUSION: There is great heterogeneity regarding the recommendations for pharmacogenetic tests from three documentary sources used by pharmacists to monitor drug therapy in the United States, Canada and France. There is an urgent need to standardize the requirements for nomenclature, description and the need to use pharmacogenetic tests to ensure proper use of drugs and these tests in the clinic.
Subject(s)
Genetic Testing/standards , Pharmacogenetics/standards , Attitude of Health Personnel , Canada , Cross-Sectional Studies , Databases, Factual , Drug Monitoring , France , Genetic Testing/statistics & numerical data , Humans , Pharmacists , Pharmacogenetics/statistics & numerical data , United StatesABSTRACT
With the exception of a few medical specialties, the implementation of pharmacogenetic tests in daily practice has thus far been limited. The Royal Dutch Pharmacists Association (KNMP) has developed pharmacogenetics-based therapeutic doserecommendations for 80 medicinal product combinations on the basis of a systematic literature review. Genotyping of patients can take place on a reactive or pre-emptive basis; the advantage of pre-emptive genotyping is that it provides genetic information the moment a medicinal product is prescribed. Clinical decision support software is crucial to implement pharmacogenetics into daily practice.
Subject(s)
Decision Support Systems, Clinical , Drug Prescriptions/standards , Pharmacogenetics/standards , Pharmacogenomic Testing/standards , Drug Dosage Calculations , Genotyping Techniques , Humans , Netherlands , Pharmacists/organization & administration , Pharmacogenetics/methods , Pharmacogenomic Testing/methods , Systematic Reviews as TopicABSTRACT
BACKGROUND: Laboratorians have the opportunity to help minimize the frequency of adverse drug reactions by implementing pharmacogenomic testing and alerting care providers to possible patient/drug incompatibilities before drug treatment is initiated. Methods combining PCR with MALDI-ToF MS have allowed for sensitive, economical, and multiplexed pharmacogenomic testing results to be delivered in a timely fashion. METHOD: This study evaluated the analytical performance of the Agena Biosciences iPLEX® PGx 74 panel and a custom iPLEX panel on a MassARRAY MALDI-TOF MS instrument in a clinical laboratory setting. Collectively, these panels evaluate 112 SNVs across 34 genes implicated in drug response. Using commercially available samples (Coriell Biorepository) and in-house extracted DNA, we determined ideal reaction conditions and assessed accuracy, precision, and robustness. RESULTS: Following protocol optimization, the Agena PGx74 and custom panels demonstrated 100% concordance with the 1000 Genomes Project Database and clinically validated hydrolysis probe genotyping assays. 100% concordance was also observed in all assessments of assay precision when appropriate QC metrics were applied. CONCLUSIONS: Significant development time was required to optimize sample preparation and instrumental analysis and 3 assays were removed due to inconsistent performance. Following modification of the manufacturer's protocol and instituting manual review of each assay plate, the Agena PGx74 and custom panel constitute a cost-effective, robust, and accurate method for clinical identification of 106 SNVs involved in drug response.
Subject(s)
Pharmacogenetics/methods , Polymorphism, Single Nucleotide , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization , Alleles , Cytochrome P-450 CYP2C19/genetics , Cytochrome P-450 CYP2C9/genetics , Humans , Molecular Diagnostic Techniques/economics , Molecular Diagnostic Techniques/instrumentation , Molecular Diagnostic Techniques/methods , Molecular Diagnostic Techniques/standards , Pharmacogenetics/economics , Pharmacogenetics/instrumentation , Pharmacogenetics/standards , Polymerase Chain Reaction/methods , Reproducibility of Results , Sensitivity and SpecificitySubject(s)
Evidence-Based Medicine/standards , Off-Label Use/standards , Pharmaceutical Preparations/standards , Pharmacogenetics/standards , Practice Guidelines as Topic/standards , United States Food and Drug Administration/standards , Drug Interactions/genetics , Evidence-Based Medicine/methods , Humans , Pharmacogenetics/methods , Pharmacogenomic Testing/methods , Pharmacogenomic Testing/standards , United States/epidemiologySubject(s)
Humans , Pharmacogenetics/standards , Psychiatry/standards , Decision Support Techniques , Pharmacogenomic Testing/standards , Psychiatry/methods , Psychotropic Drugs/pharmacology , Practice Guidelines as Topic , Pharmacogenomic Testing/methods , Mental Disorders/genetics , Mental Disorders/drug therapyABSTRACT
Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most commonly used analgesics due to their lack of addictive potential. However, NSAIDs have the potential to cause serious gastrointestinal, renal, and cardiovascular adverse events. CYP2C9 polymorphisms influence metabolism and clearance of several drugs in this class, thereby affecting drug exposure and potentially safety. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for NSAIDs based on CYP2C9 genotype (updates at www.cpicpgx.org).
Subject(s)
Anti-Inflammatory Agents, Non-Steroidal/pharmacokinetics , Cytochrome P-450 CYP2C9/genetics , Drug-Related Side Effects and Adverse Reactions/genetics , Pharmacogenetics/standards , Pharmacogenomic Testing/standards , Pharmacogenomic Variants , Anti-Inflammatory Agents, Non-Steroidal/adverse effects , Clinical Decision-Making , Consensus , Cytochrome P-450 CYP2C9/metabolism , Drug Interactions , Drug-Related Side Effects and Adverse Reactions/enzymology , Genotype , Humans , Phenotype , Predictive Value of Tests , Risk Assessment , Risk FactorsABSTRACT
Pharmacogenomics (PGx), studying the relationship between drug response and genetic makeup of an individual, is accelerating advances in precision medicine. The FDA includes PGx information in the labeling of approved drugs to better inform on their safety and effectiveness. We herein present a summary of PGx information found in 261 prescription drug labeling documents by querying the publicly available FDALabel database. A total of 362 drug-biomarker pairs (DBPs) were identified. We profiled DBPs using frequency of the biomarkers and their therapeutic classes. Four categories of applications (indication, safety, dosing and information) were discussed according to information in labeling. This analysis facilitates better understanding, utilization and translation of PGx information in drug labeling among researchers, healthcare professionals and the public.