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Preemptive Clinical Pharmacogenetics Implementation: Current Programs in Five US Medical Centers
Abstract
Although the field of pharmacogenetics has existed for decades, practioners have been slow to implement pharmacogenetic testing in clinical care. Numerous publications describe the barriers to clinical implementation of pharmacogenetics. Recently, several freely available resources have been developed to help address these barriers. In this review, we discuss current programs that use preemptive genotyping to optimize the pharmacotherapy of patients. Array-based preemptive testing includes a large number of relevant pharmacogenes that impact multiple high-risk drugs. Using a preemptive approach allows genotyping results to be available prior to any prescribing decision so that genomic variation may be considered as an inherent patient characteristic in the planning of therapy. This review describes the common elements among programs that have implemented preemptive genotyping and highlights key processes for implementation, including clinical decision support. Expected final online publication date for the Annual Review of Pharmacology and Toxicology Volume 55 is January 06, 2015. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
... A few examples of preemptive PGx testing of genetic variants associated with ADRs include HLA-B*57:01 for abacavir, HLA-B*15:02 for phenytoin, fosphenytoin, HLA-B*15:02 and HLA-A*31:01 for carbamazepine; HLA-B*15:02 and HLA-A*24:02 for lamotrigine; HLA-B*58:01 for allopurinol; CYP2C19 for clopidogrel; TPMT, NUDT15 for 6-mercaptopurine; azathioprine; and cisplatin; DPYD for fluoropyrimidines; CYP2C9 and VKORC1 for coumarin derivatives; MTHFR for methotrexate treatment; factor V Leiden for oral contraception; and CYP2D6, CYP2C19, CYP2C9 and CYP2B6 for neuropsychiatric drug prescription [15,[50][51][52][53][54][55][56]. All of the examples are enlisted to emphasize utility coverage in various domains of clinical care. ...
... Despite the increasing number of PGx studies, the use of PGx in clinical practice has been very slow due to various challenges, especially in developing countries. These challenges include limited randomized trials demonstrating improved clinical outcomes based on genotype, methodological limitations in published studies, turnaround times and availability of genotyping tests, regulatory and ethical concerns, lack of cost-effectiveness analyses, lack of education and training for health care providers, potential delays in therapy while awaiting test results, and the need for patient privacy and confidentiality [55][56][57]62]. As more evidence emerges and testing techniques advance, the cost of testing is expected to decrease, increasing accessibility [55][56][57]. ...
... These challenges include limited randomized trials demonstrating improved clinical outcomes based on genotype, methodological limitations in published studies, turnaround times and availability of genotyping tests, regulatory and ethical concerns, lack of cost-effectiveness analyses, lack of education and training for health care providers, potential delays in therapy while awaiting test results, and the need for patient privacy and confidentiality [55][56][57]62]. As more evidence emerges and testing techniques advance, the cost of testing is expected to decrease, increasing accessibility [55][56][57]. A comprehensive approach involving collaboration between healthcare professionals, regulatory bodies, and patients is necessary to promote the appropriate use of preemptive PGx testing and develop guidelines and policies [55][56][57]. ...
Adverse drug reactions (ADRs) are a significant public health concern and a leading cause of hospitalization; they are estimated to be the fourth leading cause of death and increasing healthcare costs worldwide. Carrying a genetic variant could alter the efficacy and increase the risk of ADRs associated with a drug in a target population for commonly prescribed drugs. The use of pre-emptive pharmacogenetic/omic (PGx) testing can improve drug therapeutic efficacy, safety, and compliance by guiding the selection of drugs and/or dosages. In the present narrative review, we examined the current evidence of pre-emptive PGx testing-based treatment for the prevention of ADRs incidence and hospitalization or emergency department visits due to serious ADRs, thus improving patient safety. We then shared our perspective on the importance of preemptive PGx testing in clinical practice for the safe use of medicines and decreasing healthcare costs.
... In the US, 18% of all prescriptions are influenced by actionable PGx genes, with 90-99% of the population having at least one high-risk variant for established genes [3,[5][6][7]. Common reasons for conducting PGx services include toxicity concerns, side effects, medication nonresponders (e.g., the lack of efficacy), a family history of significant variants, preemptive to treatment, or incidental research findings [8]. These concerns led to the U.S. Food and Drug Administration (FDA) to include pharmacogenomic labeling information for over 200 medications that have a particular gene-drug interaction, including some that warn of potential life-threatening situations via "Black Box warnings" [9,10]. ...
... Often a reactive test will assess only one gene-drug pair; thus, the future utility of the results is limited in accessibility to other prescribers. Contrarily, preemptive PGx testing is proactive, performed to help avoid adverse medication side effects and improve medication efficacy before a specific medication is selected and taken by the patient [6,14,15]. Preemptive testing provides information that may be useful later, as the health conditions and medication needs of the patient change, yet their genotype will most likely remain the same [15,16]. Preemptive pharmacogenetic testing is beginning to be utilized in a number of patient diagnoses, such as oncology, cardiology, hematology, as well as patient populations (e.g., pediatrics). ...
... Preemptive pharmacogenetic testing is beginning to be utilized in a number of patient diagnoses, such as oncology, cardiology, hematology, as well as patient populations (e.g., pediatrics). As PGx testing continues to decrease in cost, preemptive testing may be a more cost-effective approach to patient care [3,6,13]. For example, conducting PGx testing in a child would have great utility as the child matures into an adult, thus providing metabolic drug information over their lifetime. ...
(1) Background: This retrospective analysis utilizing electronic medical record (EMR) data from a tertiary integrated health system sought to identify patients and prescribers who would benefit from pharmacogenomic (PGx) testing based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. (2) Methods: EMR data from a clinical research data warehouse were analyzed from 845,518 patients that had an encounter between 2015 and 2019 at an academic medical center. Data were collected for 42 commercially available drugs with 52 evidence-based PGx guidelines from CPIC. Provider data were obtained through the EMR linked by specialty via national provider identification (NPI) number. (3) Results: A total of 845,518 patients had an encounter in the extraction period with 590,526 medication orders processed. A total of 335,849 (56.9%) patients had medication orders represented by CPIC drugs prescribed by 2803 providers, representing 239 distinct medications. (4) Conclusions: The results from this study show that over half of patients were prescribed a CPIC actionable medication from a variety of prescriber specialties. Understanding the magnitude of patients that may benefit from PGx testing, will enable the development of preemptive testing processes, physician support strategies, and pharmacist workflows to optimize outcomes should a PGx service be implemented.
... Such genetic tests are typically restricted to a small number of well-characterised gene variants with pharmacogenomic relevance (see Australian Pharmacist May 2015). There are some exceptions such as paternity tests and 23andMe, 3 which is a high-throughput microarray test that simultaneously examines thousands of gene variants. The 23andMe genetesting kit is now being marketed through over 600 UK pharmacies. ...
... These are the myDNA gene test (previously DNAdose), 4 available through medical practitioners or Chemmart pharmacies, and Sonic Genetics' Pharmacogenetic Screen gene test, also known as Pharmaco Profile, again available through medical practitioners. 5 The third example we consider is the 23andMe gene test, 3 sold through pharmacies in the UK as noted above and available direct-to-consumers in Australia, the US and other countries over the internet. ...
... 5 However collection of DNA for pharmacogenetic testing can also be done on the spot in a community pharmacy 4 or by customers at home without the need for assistance. 3 The 23andMe gene test uses DNA obtained from a saliva sample collected in a tube labelled with the consumer's specific barcode. 3 The myDNA test uses DNA obtained by a quick and painless procedure in which a simple cheek swab ('buccal' swab) is performed using a cotton bud. ...
Shifts in global approaches to personalised health care and patient-centred medicine are placing new emphasis on the need to take into account a person's individual genetic factors, along with their lifestyle and environmental exposures, in order to optimise health care.
... To date, consortia such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG) have published genotype-based guidelines for over a hundred gene-drug pairs, providing a robust and evidence-backed framework to facilitate the integration of PGx into everyday clinical practice (Relling and Klein, 2011;Bank et al., 2018;Relling et al., 2020;Abdullah-Koolmees et al., 2021). Remarkably, it is estimated that over 90% of the population carries at least one actionable pharmacogenomic variant, indicating the vast potential of PGx testing in guiding drug therapy and reducing the risk of ADRs (Dunnenberger et al., 2015;Pirmohamed, 2023). Thus, when contemplating a broad implementation of PGx testing, it is important to select a technology that is both widely accessible and cost-effective. ...
... This approach has the potential to significantly improve treatment outcomes, reduce adverse drug reactions, and ultimately lower treatment costs (Pirmohamed, 2023). It is estimated that over 90% of the population carries at least one actionable pharmacogenomic variant (Dunnenberger et al., 2015;Pirmohamed, 2023). Furthermore, PGx information is already actionable: the DPWG and CPIC consortia have to date curated dosing guidelines based on genetics for over 140 drugs (Bank et al., 2018;Abdullah-Koolmees et al., 2021). ...
Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay’s performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes.
Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets.
Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance.
Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.
... The concept of clinical pharmacogenetic (PGx) testing was introduced in the early 1990s; yet, it is still primarily limited to large academic medical centers, minimizing the number of patients with access to this important component of precision medicine. 1,2 In addition, European or Asian ancestral groups have been the most extensively studied in genetic association analyses; meanwhile, patients of African descent have a higher frequency of genetic variants that could influence their drug response compared to those of European descent. 3,4 Therefore, clinical PGx implementation may exacerbate health disparities because its patterns are based on discovery work conducted mostly in European or Asian ancestral populations. ...
... 6,7 Therefore, with the necessary tools and guidance to support a preemptive model, implementation of pharmacogenomics can be more fully realized. 2,8 Drugs with PGx guidelines or recommendations available (referred to as PGx drugs) are often off-patent and less expensive than newer counterparts. 9 We have previously found that medically underserved patients are prescribed PGx medications at a higher frequency and have fewer encounters with healthcare providers compared to patients with better access to health care. ...
Previous findings suggest that medically underserved patients are prescribed medications with pharmacogenetic (PGx) guidelines at a high frequency. Thus, underserved patients may especially benefit from PGx testing, but little evidence exists regarding the effect of testing in this population. This pilot study aimed to generate key feasibility data and explore clinical outcomes of PGx implementation in underserved populations. Black and Latino patients were recruited from an outpatient clinic and underwent PGx testing. Feasibility measures included enrollment metrics and actionable genotype frequencies. The primary clinical outcome was patient medication treatment satisfaction 6 months after testing. Implementation outcomes included the number of healthcare provider encounters and medication changes within the 6‐month follow‐up. Effectiveness outcomes included medication adherence, patient‐perceived test value, and time spent discussing medications with providers. Ninety‐nine patients completed the study. Proton‐pump inhibitors were the most frequent PGx drug class prescribed at baseline (61%) followed by nonsteroidal anti‐inflammatory drugs (36%). Patients with an actionable genotype constituted 96% of the population, while 28% had an actionable genotype related to their PGx drug. Patient treatment satisfaction significantly increased over the 6 months after PGx testing. In addition, medication adherence and the number of provider encounters significantly increased over the study period. In a pilot study, preemptive PGx testing was feasible in primary care clinics, improved patient treatment satisfaction and adherence and increased the number of provider encounters in medically underserved patients. Future clinical trials are warranted to assess the long‐term effects of PGx testing in a larger diverse patient population.
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... /2023 Abdullah- Koolmees et al., 2021). Remarkably, it is estimated that over 90% of the population carries at least one actionable pharmacogenomic variant, indicating the vast potential of PGx testing in guiding drug therapy and reducing the risk of ADRs (Dunnenberger et al., 2015;Pirmohamed, 2023). Thus, when contemplating a broad implementation of PGx testing, it is important to select a technology that is both widely accessible and cost-effective. ...
... This approach has the potential to significantly improve treatment outcomes, reduce adverse drug reactions, and ultimately lower treatment costs (Pirmohamed, 2023). It is estimated that over 90% of the population carries at least one actionable pharmacogenomic variant (Dunnenberger et al., 2015;Pirmohamed, 2023). Furthermore, PGx information is already actionable: the DPWG and CPIC consortia have to date curated dosing guidelines based on genetics for over 140 drugs (Bank et al., 2018;Abdullah-Koolmees et al., 2021). ...
Background
Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction.
However, establishing clinical reporting workflows requires a thorough evaluation of the assay’s performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes.
Methods
To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets.
Results
In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance.
Conclusion
Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.
... (van der Wouden et al, 2017) In pre-emptive PGx, patient-specific CDSS alerts prompt and guide clinicians to use genetic information when prescribing drugs with known genetically-determined ADRs. (Dunnenberger et al, 2015;Overby et al, 2014) PGx may be implemented either reactively on a gene-by-gene basis at the time of prescribing a drug, or pre-emptively where a single sample is assessed for several pharmacogenes simultaneously with the results stored for future prescribing encounters. Reactive implementation is expensive and has a slow turnaround time and is unsuitable in situations where rapid drug initiation is required. ...
... interoperability requirements along with robust and continuous updating of evidence are rigorously assessed before deciding on the PGx service provider. The significant costs associated with the use of PGx in clinical practice are now in the domain of decision support, ITintegration, and interoperability, rather than in laboratory genetic testing.(Dunnenberger et al, 2015; van der Wouden et al, 2017) Informatics builds within the EHR are easier for a single genedrug pair as opposed to the multiple pairs and networks that form as drug interactions and clinical factors are also considered. However, the costeffectiveness data on the pre-emptive panel approach must be assessed, particularly when considering i ...
Precision medicine envisages the integration of an individual’s clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.
... Pharmacogenomics (PGx) benefits medication management (Gharani et al., 2013;Dunnenberger et al., 2015;Relling and Evans, 2015;Zhang et al., 2015;Bush et al., 2016;Relling et al., 2017;Bank et al., 2018); however, pharmacogenetic annotation is often quite complex (Supplementary Figure S1). Functional PGx annotation and corresponding clinical PGx recommendations rely on star (*) allele annotation (Caudle et al., 2014;Kalman et al., 2016); star alleles are often defined by more than one genetic variant (Gaedigk et al., 2018;Gaedigk et al., 2020;Gaedigk et al., 2021); when the star alleledefining variants are heterozygous, phased haplotype information is needed to resolve the annotation. ...
Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.
... Whereas there are hundreds of reported gene-drug associations with variable levels of evidence, 97% of people in the United States tested with a targeted, clinical 12-gene pharmacogenomic panel carry at least one actionable variant. 1 The utility of these variants includes increasing accuracy in drug dosing and selection as well as reducing adverse drug events and improving treatment efficacy. [2][3][4] Many studies have focused on understanding provider knowledge and comfort with implementing clinical pharmacogenomic testing. ...
Pharmacogenomics has the potential to inform drug dosing and selection, reduce adverse events, and improve medication efficacy; however, provider knowledge of pharmacogenomic testing varies across provider types and specialties. Given that many actionable pharmacogenomic genes are implicated in cardiovascular medication response variability, this study aimed to evaluate cardiology providers' knowledge and attitudes on implementing clinical pharmacogenomic testing. Sixty‐one providers responded to an online survey, including pharmacists (46%), physicians (31%), genetic counselors (15%), and nurses (8%). Most respondents (94%) reported previous genetics education; however, only 52% felt their genetics education prepared them to order a clinical pharmacogenomic test. In addition, most respondents (66%) were familiar with pharmacogenomics, with genetic counselors being most likely to be familiar ( p < 0.001). Only 15% of respondents had previously ordered a clinical pharmacogenomic test and a total of 36% indicated they are likely to order a pharmacogenomic test in the future; however, the vast majority of respondents (89%) were interested in pharmacogenomic testing being incorporated into diagnostic cardiovascular genetic tests. Moreover, 84% of providers preferred pharmacogenomic panel testing compared to 16% who preferred single gene testing. Half of the providers reported being comfortable discussing pharmacogenomic results with their patients, but the majority (60%) expressed discomfort with the logistics of test ordering. Reported barriers to implementation included uncertainty about the clinical utility and difficulty choosing an appropriate test. Taken together, cardiology providers have moderate familiarity with pharmacogenomics and limited experience with test ordering; however, they are interested in incorporating pharmacogenomics into diagnostic genetic tests and ordering pharmacogenomic panels.
... [3][4][5] When 12 pharmacogenes with at least one known, actionable, inherited variant are considered, over 97% of the U.S. population has at least one potentially actionable finding (e.g. presence of a CYP2C19 diplotype containing a *2 , *3 or *17 allele) 6 with an estimated impact on nearly 75 million prescriptions. 7 Chanfreau-Coffinier et al 8 have estimated that almost all veterans carry an actionable variant, and more than half had been exposed to a drug that is greatly affected by these variants. ...
Objectives:
Pharmacogenetics (PGx) is increasingly important in individualizing therapeutic management plans, but is often implemented apart from other types of medication clinical decision support (CDS). The lack of integration of pharmacogenetics into existing CDS may result in incomplete interaction information, which may pose patient safety concerns. We sought to develop a cloud-based orchestrated medication CDS service that integrates PGx with a broad set of drug screening alerts and evaluate it through a clinician utility study.
Methods:
We developed the PillHarmonicsTM service for implementation per the CDS Hooks protocol, algorithmically integrating a wide range of drug interaction knowledge using cloud-based screening services from First Databank (drug-drug/allergy/condition), PharmGKB (drug-gene), and locally curated content (drug-renal/hepatic/race). We performed a user study, presenting 13 clinicians and pharmacists with a prototype of the system's usage in synthetic patient scenarios. We collected feedback via a standard questionnaire and structured interview.
Results:
Clinician assessment of PillHarmonics via the Technology Acceptance Model questionnaire shows significant evidence of perceived utility. Thematic analysis of structured interviews revealed that aggregated knowledge, concise actionable summaries, and information accessibility were highly valued, and that clinicians would use the service in their practice.
Conclusions:
Medication safety and optimizing efficacy of therapy regimens remain significant issues. A comprehensive medication CDS system that leverages patient clinical and genomic data to perform a wide range of interaction checking and present a concise and holistic view of medication knowledge back to the clinician, is feasible and perceived as highly valuable for more informed decision-making. Such a system can potentially address many of the challenges identified with current medication related CDS.
... Pharmacogenomics (PGx) holds the potential to improve medication management by increasing efficacy and by reducing toxicity [1][2][3][4][5][6][7]. Translating pharmacogenomic research into clinical care, however, requires a robust inter-disciplinary infrastructure [8,9]. ...
Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool (www.coriell.org/StarAllele/Search). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12864-024-09994-6.
... Studies have suggested that approximately 90-99% of the population may contain an actionable variant for a gene with an established drug association, and argue for preemptive pharmacogenomic testing [32,33]. In addition, the discovery-enabled capacity of pharmacogenomic testing with next-generation sequencing (NGS) methods may provide further benefit over traditional genotyping methods developed to evaluate variants, particularly for patients of genetic ancestries not widely represented in benchmark studies. ...
Genetic alterations between individuals contribute to variations in drug response and susceptibility to adverse drug reactions. Testing for these alterations is accomplished via pharmacogenetic and pharmacogenomic molecular methods, with PCR-based, microarray, and next-generation sequencing platforms available in many clinical laboratories. The integration of this information into clinical practice offers the prospect of tailoring drug therapy to individual genetic profiles, improving patient outcomes while minimizing adverse events. Despite the promise, many challenges persist in the implementation and rapid evolvement of these methodologies. We present an overview of pharmacogenetic and pharmacogenomics methods, highlight specific examples of well-established pharmacogenetic associations, and summarize available resources for clinical testing recommendations.
... Moreover, several methods for developing and applying pharmacogenomics and personalizing drug therapy have been proposed [89]. Despite this, the implementation of pharmacogenomics in routine clinical practice has been sparse, and very few centers currently include pharmacogenetic tests in routine clinical care [90][91][92][93][94][95]. Several factors can explain this finding. ...
Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.
... Pharmacogenomics takes observed variability into account and describes how to use genetic information for the safe and efficacious use of medicine. Clinical pharmacogenomic (PGx) testing for drug-gene pairs with actionable practice guidelines has been widely recognized as a tool for guiding clinicians in selecting drugs and drug doses predicted to result in optimal treatment outcomes [1,2]. Single nucleotide polymorphisms (SNPs) in drug metabolising enzymes confer different activities and functionality of enzymes ranging from normal metabolizers (NM), intermediate metabolizers (IM), poor metabolizers (PM), and ultra-rapid metabolizers (UM) [3]. ...
Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm ® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm ® . We then used GenoPharm ® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm ® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm ® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.
... Variation in genes involved in drug response (PGx genes) is common within the human population, with a recent review providing evidence that 97.8% of people worldwide are likely to carry an actionable genetic variant in a PGx gene (Pirmohamed, 2023). Furthermore, over half the drugs currently prescribed in clinical practice are metabolised by PGx genes and are affected by one or more PGx variants (Dunnenberger et al., 2015;Kimpton et al., 2019). ...
Pharmacogenetics (PGx) is the study and application of how interindividual differences in our genomes can influence drug responses. By evaluating individuals’ genetic variability in genes related to drug metabolism, PGx testing has the capabilities to individualise primary care and build a safer drug prescription model than the current “one-size-fits-all” approach. In particular, the use of PGx testing in psychiatry has shown promising evidence in improving drug efficacy as well as reducing toxicity and adverse drug reactions. Despite randomised controlled trials demonstrating an evidence base for its use, there are still numerous barriers impeding its implementation. This review paper will discuss the management of mental health conditions with PGx-guided treatment with a strong focus on youth mental illness. PGx testing in clinical practice, the concerns for its implementation in youth psychiatry, and some of the barriers inhibiting its integration in clinical healthcare will also be discussed. Overall, this paper provides a comprehensive review of the current state of knowledge and application for PGx in psychiatry and summarises the capabilities of genetic information to personalising medicine for the treatment of mental ill-health in youth.
... This progress is evident in several pioneering healthcare institutions from North America and Europe where PGx has been successfully integrated into routine clinical practice. 2,3 These initiatives are strongly backed by the accumulating evidence-based PGx clinical guidelines and supporting resources developed by professional organizations and consortia, such as the Clinical Pharmacogenetics Implementation Consortium in the United States, 4 the Dutch Pharmacogenetics Working Group, 5 the Canadian Pharmacogenomics Network for Drug Safety, 6 and the French Network of Pharmacogenetics. 7 In the past decade, there has been a notable surge in PGx research specifically targeting non-European populations. ...
Pharmacogenomics (PGx) implementation into clinical care is rapidly increasing in China. However, the extent to which the public understands PGx testing and important knowledge domains requiring patient education or counseling remains unclear. To address this, we created and validated the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy (MAPL‐C). The MAPL‐C was developed by translating English MAPL to Chinese following cross‐cultural translation guidelines. An online survey validated the MAPL‐C and assessed Chinese individuals' PGx literacy. Validation analyses and associations with participants’ characteristics were quantified. Of 959 high‐quality responses, the majority of respondents were Han Chinese (96.3%), male (54.5%), aged 18‐29 years (70.9%), residing in China (97.3%), and had received college or higher education (95.0%). Out of 15 starting items developed to query specific predefined knowledge domains, two uninformative items were excluded, resulting in a 13‐item MAPL‐C. Chinese participants’ MAPL‐C performance was best explained by a three‐factor model, encompassing PGx concepts and function, testing limitations, and privacy. Higher MAPL‐C performance was associated with younger age, higher education, and previous genetic testing experience. Correct response rates for questions related to testing limitations were lower than other domains. The creation and validation of the MAPL‐C fills a gap in determining PGx knowledge among Chinese speakers, quantifying PGx literacy within a Chinese cohort and identifying response patterns and knowledge gaps. The MAPL‐C can be useful in clinical practice to guide patient counseling, assess PGx education interventions, and quantify PGx knowledge in relation to outcomes in research studies involving Chinese participants.
... Genetic variation in PGxs, affecting drug response, is common (12). In the USA, ~50% of prescriptions involve actionable germline PGxs (13), and in the UK, 58% of patients receive drugs influenced by pharmacogenetic polymorphisms (14). Elderly individuals, often requiring drug therapy, are exposed to pharmacogenomic-guided drugs (~90% of those over 70 years) (14). ...
Pharmacogenetics and pharmacogenomics (PGx) have revolutionized personalized medicine by studying DNA's role in drug response variability. While "pharmacogenetics" often relates to genes affecting drug metabolism, "pharmacogenomics" encompasses all genome-related drug responses. The distinction is arbitrary, and both terms are used interchangeably. PGx influences drug efficacy, safety, and dosage, allowing for personalized treatments. Its history dates back to 510 B.C., with Pythagoras noting differential reactions to fava beans. Despite international clinical guidelines, PGx research has gaps, especially in regions like Iraq, where genetic diversity and frequency data are lacking. Drug responses result from both pharmacokinetic and pharmacodynamic factors, with GWAS aiding gene-drug interaction discovery. Genetic variations in PGx are prevalent, impacting over 50% of prescriptions in the USA and 58% in the UK. PGx influences drug dosages, exemplified by warfarin's sensitivity to CYP2C9 and VKORC1 variants. It also plays a role in adverse drug reactions (ADRs), with immune-mediated ADRs and HLA alleles studied extensively. Genotyping has significantly reduced ADRs, as seen with abacavir hypersensitivity. Despite challenges, PGx is slowly integrating into clinical practice. Pre-emptive genotyping and panel-based testing hold promise, but validation is essential. PGx has also revolutionized drug development, doubling success rates by selecting genetically supported drug targets. PGx's future involves addressing ethnic diversity gaps in genomics data and embracing polygenic risk scores. Its potential to shape healthcare and offer tailored therapies makes it a pivotal player in the future of medicine. In conclusion, PGx is a transformative field that enhances drug therapy, drug development, and disease risk assessment. Overcoming challenges, particularly related to clinical implementation and genetic diversity, is essential to realize the full potential of PGx in shaping the future of healthcare globally.
... 2 Background Pharmacogenomics (PGx) holds the potential to improve medication management by increasing efficacy and by reducing toxicity [1][2][3][4][5][6][7]. Translating pharmacogenomic research into clinical care, however, requires a robust inter-disciplinary infrastructure [8,9]. ...
Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n=3202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.
... But since medical practitioners are occupied with taking care of patients, they should not need to use their working time to read through numerous papers every day to keep themselves up-to-date. Recent surveys showed that only 29% of the clinical professionals received education in PGx, and the rest had their training in the pre-genomic era [3]. This is one of the reasons for resistance of some clinical practitioners to consider PGx during the drug prescription. ...
In the last few decades, precision medicine became a highly weighted subject as the risk of side effects grew with the increasing drug use. improve the safety of drug therapy. The newly introduced software module GraphSAW2-DWHBuilder creates the graph-based data warehouse. For that, molecular data from various sources is assembled in a graph database. Furthermore, an update strategy was developed to ensure that only the latest version of the data is used. To eliminate redundancies and to guarantee efficient querying, a mapper strategy was established. Another new module named GraphSAW2-Check is embedded in an existing drug therapy safety workflow used in hospitals. It contains methods for the pharmacogenetic check, which access the molecular data warehouse of the GraphSAW2-DWHBuilder and execute queries on the graph. These queries contain the drugs and the molecular data of interest and search for connections that represent toxic associations between them. If a connection is found, a warning will be issued to the medical practitioner, who can then reconsider their prescription. The results reveal the added value of molecular data integration to the drug therapy safety.
... Pharmacogenomics (PGx) benefits medication management [1][2][3][4][5][6][7], however, pharmacogenetic annotation is often quite complex. Functional PGx annotation and corresponding clinical PGx recommendations rely on star (*) allele annotation [8,9]; star alleles are often defined by more than one genetic variant [10][11][12]; and when the star allele defining variants are heterozygous, phased haplotype information is needed to resolve the annotation. ...
Long-read sequencing technologies offer new opportunities to generate high confidence phased whole genome sequencing data for robust pharmacogenetic annotation. Here we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.
... Pharmacogenetics (relating to a single gene) and pharmacogenomics (relating to multiple genes) are key to understanding how to use medications more safely and effectively, ensuring better compliance, and avoiding ADRs. Indeed, the field of pharmacogenomics has been identified as one of great promise for personalized or precision medicine (5). Rapid technological advances in genomics and a sharp reduction in the costs of testing have produced a new generation of studies focused on drug variability and helped to introduce personalized or precision medicine into clinical practice. ...
The past two decades have seen enormous advancements in medical knowledge around the role of genetic factors of variability, both in human disease and drug response. This knowledge is increasingly being translated into guidelines that inform drug dosing, monitoring for efficacy and safety, and determining the suitability of specific agents to treat patients. Health Canada and the U.S. Food and Drug Administration have recommended using genetic information to guide dosing for more than 20 drugs. There are no current, comprehensive paediatric guidelines to assist health care professionals in the use of genetics to inform medication dosing, safety, and efficacy in children, and such guidance is urgently needed. This statement helps to guide clinician understanding of the role of pharmacogenetics and how to use this information when prescribing medications in paediatrics.
... La pharmacogénétique (liée à un seul gène) et la pharmacogénomique (liée à de multiples gènes) sont essentielles pour comprendre comment utiliser les médicaments de manière plus sécuritaire et plus efficace, s'assurer d'une meilleure adhésion et éviter les RIM. En fait, le domaine de la pharmacogénomique est considéré comme très prometteur pour la médecine personnalisée ou la médecine de précision (5). Les progrès technologiques rapides de la génomique et la forte réduction des coûts des tests ont favorisé une nouvelle génération d'études axées sur la variabilité des médicaments et ont contribué à intégrer la médecine personnalisée et la médecine de précision à la pratique clinique. ...
Depuis vingt ans, le savoir médical sur le rôle des facteurs génétiques de variabilité a énormément évolué, tant à l'égard des maladies humaines que de la réponse aux médicaments. Ce savoir se traduit de plus en plus par des directives qui influent sur la posologie, la surveillance de l'efficacité et de l'innocuité et la détermination de la pertinence d'agents particuliers pour traiter les patients. Santé Canada et la Food and Drug Administration des États-Unis recommandent d'utiliser l'information génétique pour orienter la posologie de plus de 20 médicaments. Il n'existe actuellement pas de directives pédiatriques complètes pour aider les professionnels de la santé à utiliser la génétique afin d'établir la posologie, l'innocuité et l'efficacité des médicaments chez les enfants, et ces directives s'imposent d'urgence. Le présent document de principes aide le clinicien à comprendre le rôle de la pharmacogénétique et à utiliser l'information qu'il en tire pour prescrire des médicaments en pédiatrie.
... Similar frequencies have been reported in other study groups across different gene panels. According to the PG4KDS study, nearly 98.5% Caucasian and 99.1% African people in the United States carry at least one high-risk genotype across 12 pharmacogenes (Dunnenberger et al., 2015). The eMERGE-PGx study across 82 pharmacogenes reported that 96.2% of the participants carry at least one actionable genotype respectively (Bush et al., 2016). ...
Background: Population genomic studies of individuals of Indigenous ancestry have been extremely limited comprising <0.5% of participants in international genetic databases and genome-wide association studies, contributing to a “genomic gap” that limits their access to personalised medicine. While Indigenous Australians face a high burden of chronic disease and associated medication exposure, corresponding genomic and drug safety datasets are sorely lacking.
Methods: To address this, we conducted a pharmacogenomic study of almost 500 individuals from a founder Indigenous Tiwi population. Whole genome sequencing was performed using short-read Illumina Novaseq6000 technology. We characterised the pharmacogenomics (PGx) landscape of this population by analysing sequencing results and associated pharmacological treatment data.
Results: We observed that every individual in the cohort carry at least one actionable genotype and 77% of them carry at least three clinically actionable genotypes across 19 pharmacogenes. Overall, 41% of the Tiwi cohort were predicted to exhibit impaired CYP2D6 metabolism, with this frequency being much higher than that for other global populations. Over half of the population predicted an impaired CYP2C9, CYP2C19, and CYP2B6 metabolism with implications for the processing of commonly used analgesics, statins, anticoagulants, antiretrovirals, antidepressants, and antipsychotics. Moreover, we identified 31 potentially actionable novel variants within Very Important Pharmacogenes (VIPs), five of which were common among the Tiwi. We further detected important clinical implications for the drugs involved with cancer pharmacogenomics such as thiopurines and tamoxifen, immunosuppressants like tacrolimus and certain antivirals used in the hepatitis C treatment due to potential differences in their metabolic processing.
Conclusion: The pharmacogenomic profiles generated in our study demonstrate the utility of pre-emptive PGx testing and have the potential to help guide the development and application of precision therapeutic strategies tailored to Tiwi Indigenous patients. Our research provides valuable insights on pre-emptive PGx testing and the feasibility of its use in ancestrally diverse populations, emphasizing the need for increased diversity and inclusivity in PGx investigations.
... ADRs are a serious clinical problem, with 2.2 million ADRs annually (100,000 of which lead to fatal consequences), and they have a direct medical cost of 200 billion US dollars in the United States (US) [2]. Although big PGx initiatives have demonstrated PGx's utility in the clinical setting [3][4][5][6] and the cost-effectiveness of PGx testing has also been established [7], mostly, PGx diagnostic is implemented in a reactive way, testing only those genes related with the drug which is going to be prescribed. However, pre-emptive PGx testing by a single test covering a sufficient number of medications and future medication exposure may be easier to implement and more cost-effective than reactive PGx testing. ...
The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.
... Currently, the slow clinical adoption of PGx is primarily due to barriers that delay its introduction into clinical practice. The lack of standardized PGx guidelines and their difficult interpretation by clinicians who have been resistant to PGx information are just some of these obstacles (Swen et al., 2007;Dunnenberger et al., 2015). (Swen et al., 2008Caudle et al., 2014;Abdullah-Koolmees et al., 2020). ...
The use of pharmacogenetic guidelines in personalizing treatments has shown the potential to reduce interindividual variability in drug response by enabling genotype-matched dosing and drug selection. However, other important factors, such as patient gender, may interact strongly with pharmacogenetics in determining the individual profile of toxicity and efficacy, but are still rarely considered when planning pharmacological treatment. The literature indicates that males and females respond differently to drugs, with women being at higher risk for toxicity and having different plasma exposure to drugs at standard doses. Recent studies have shown that pharmacogenetic variants may have different predictive value in different sexes, as in the case of treatment with opioids, ACE inhibitors, or proton pump inhibitors. Of particular interest is the case of treatment with fluoropyrimidines for cancer. A significant increase in toxicity has been described in female patients, with a more pronounced effect of specific DPYD and TYMS polymorphisms also noted. This manuscript reviews the major findings in the field of sex-specific pharmacogenomics. Significance Statement Interindividual variability in drug response is an emerging issue in pharmacology. The genetic profile of patients, as well as their gender, may play a role in the identification of patients more exposed to the risk of adverse drug reactions or poor efficacy. This article reviews the current state of research on the interaction between gender and pharmacogenetics in addressing interindividual variability.
Background: The implementation of pharmacogenetic (PGx) testing may contribute to health disparities if access to testing is inequitable, as medically underserved patients are prescribed higher rates of drugs with PGx guidelines and often experience the benefits of emerging health technologies last. Limited research has evaluated potential implementation of PGx testing in populations who are medically underserved and none have evaluated their preferences regarding PGx test characteristics and cost. Our study endeavored to assess the willingness to pay for PGx testing and key PGx test preferences in a nationwide cohort of medically underserved respondents.
Methods: A survey was developed to assess willingness to pay and preferences for PGx testing through a discrete choice experiment (DCE). Five attributes of PGx tests were included in the DCE: doctor recommendation, wait time, number of actionable results, benefit of the test (avoid a side effect or address a health problem), and out-of-pocket cost. A convenience sample of U.S. adults with an average yearly household income of $42,000 or less was collected utilizing an online survey fielded by Qualtrics Research Services (Provo, UT). For the DCE analysis, conditional logit and mixed-logit regression models were utilized to determine relative utility of attributes and levels, conditional relative importance for each attribute, and marginal willingness to pay.
Results: Respondents completed the survey with an 83.1% response completion rate. Following quality control procedures, 1,060 respondents were included in the final nationwide cohort. Approximately, 82% of respondents were willing to pay less than $100 for PGx testing, and a strong price ceiling was identified at $200. Out-of-pocket cost was the attribute identified as having the greatest relative importance on choice, while wait time had the lowest importance. Greater utility was observed if the PGx test was doctor recommended, had a higher number of actionable results, and resolved major or minor health problems compared with avoiding side effects.
Conclusion: This first-of-its-kind study provides important insights into the willingness to pay for PGx testing and PGx test preferences of a large medically underserved population. Applying these findings can potentially lead to improvements in the successful implementation of PGx testing in this population.
Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.
Introduction:
The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.
Areas covered:
We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.
Expert opinion:
While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.
Pharmacogenomics has a potential to improve and individualize treatment of cardiovascular diseases. In the past couple of decades, strong evidence emerged to inform PGx guided drug prescribing, dose selection, and clinical implementation of some common cardiovascular drug classes such as anticoagulants, antiplatelets, and statins. This chapter discusses evidence, including several clinical trials, treatment algorithms, genetic variants with demonstrated clinical impact and guidelines related to these drug and other cardiovascular drug classes.
Introduction
Preemptive pharmacogenomic (PGx) testing is on the rise among United States health care centers, with the majority of testing performed in the primary care setting. For broader implementation, there is a call for descriptions of the implementation and workflow of successful PGx programs in a large variety of health care settings.
Objective
The purpose of this study was to describe the implementation and initial outcomes of preemptive PGx (11‐gene, multi‐panel) testing in inpatient workflow at a Veterans Affairs medical center.
Methods
The inpatient clinical pharmacist incorporated patient screening, informed consent, and PGx lab ordering into their daily workflow in March 2023. Included adult patients had to be enrolled into the facility's primary care program and able to provide informed consent. Patients were excluded if they had a history of bone marrow or liver transplant, were consulted for palliative or hospice care, or had altered mental status at the time of screening. A retrospective chart review was used to collect demographics and PGx results from March to August 2023.
Results
There were 247 patients screened for PGx testing in the 6‐month study period. Of these, 74 already had PGx performed, 31 declined or deferred testing, and 142 consented to testing. Laboratory blood draw was not performed as ordered on 12 patients, leaving 130 samples with results. Of 130 patients, 129 (99%) had an actionable PGx variant, with most having multiple variants: 1 variant (6%), 2 variants (15%), 3 variants (32%), 4 variants (24%), 5 variants (18%), 6 variants (3%). At the time of follow‐up, 64 (49%) patients were prescribed an affected medication: 1 medication (38%), 2 medications (8%), 3 medications (3%).
Conclusion
Incorporating preemptive PGx testing into inpatient workflow is feasible in a rural facility with a significant proportion of patients being affected by the results.
Aim: To advance clinical adoption and implementation of pharmacogenomics (PGx) testing, barriers and facilitators to these efforts must be understood. This study identified and examined barriers and facilitators to active implementation of a PGx program across multiple clinic settings in an academic healthcare system. Materials & methods: 28 contributors to the PGx implementation (e.g., clinical providers, informatics specialists) completed an interview to elicit their perceptions of the implementation. Results: Qualitative analysis identified several barriers and facilitators that spanned different stages of the implementation process. Specifically, unclear test payment mechanisms, decision support tool development, rigid workflows and provider education were noted as barriers to the PGx implementation. A multidisciplinary implementation team and leadership support emerged as key facilitators. Furthermore, participants also suggested strategies to overcome or maintain these factors. Conclusion: Assessing real-world implementation perceptions and suggested strategies from a range of implementation contributors facilitates a more comprehensive framework and best-practice guidelines for PGx implementation.
The volume and complexity of biological and biomedical research continues to grow exponentially with cutting-edge technologies such as high-throughput sequencing. Unfortunately, bioinformatics analysis is often considered only after data have been generated, which significantly limits the ability to make sense of complex big data. This unique book introduces the idea of No-Boundary Thinking (NBT) in biological and biomedical research, which aims to access, integrate, and synthesize data, information, and knowledge from bioinformatics to define important problems and articulate impactful research questions. This interdisciplinary volume brings together a team of bioinformatics specialists who draw on their own experiences with NBT to illustrate the importance of collaborative science. It will help stimulate discussion and application of NBT, and will appeal to all biomedical researchers looking to maximize their use of bioinformatics for making scientific discoveries.
Introduction
Pharmacogenomics (PGx) testing uses a patient's deoxyribonucleic acid (DNA) profile to tailor medications with the goal of preventing adverse drug reactions and improving pharmacotherapy outcomes. Despite the availability of evidence‐based guidelines that assist with interpretation of PGx results, PGx testing has not been widely adopted.
Objective
To describe how a multidisciplinary PGx clinic was implemented within the University of Pennsylvania Health System (Penn Medicine) including the clinical workflow, challenges to implementation, and future directions.
Methods
This project qualified as Quality Improvement by the University of Pennsylvania's Institutional Review Board and adheres to the Standards for Quality Improvement Reporting Excellence (SQUIRE) 2.0 guidelines. Clinic metrics were collected from February 2019 until December 2022. Data collected included patient demographics; the timing of PGx test ordering and appointments; number and frequency of actionable PGx phenotypes; number of current or historical medications impacted by PGx test results; and patient's out‐of‐pocket cost for PGx test.
Results
Of the 69 patients included, the majority were female (58%), white (84%), with a mean age of 48 years. The overall time between the dates of the PGx test order and clinic visit was 37 days. The time between the dates of the PGx test order and the PGx test results were generated was 18 days. All patients had at least one actionable PGx phenotype and 74% had three or more. The most frequent actionable phenotypes were found in the cytochrome P450 PC19 ( CYPC19 ) (60%) and CYP2D6 (58%) genes. The percentage of patients that had drug‐gene interactions that affected their current medications and explained historical medication intolerances were 25% and 17%, respectively. Out‐of‐pocket costs were less than $300 for most patients who had a PGx test ordered by the clinic physician.
Conclusion
This paper has established a sustainable PGx clinic workflow with dedicated personnel. In the future we intend to increase the availability of our services.
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Introduction:
Response to medications can differ widely among individual patients. Adverse drug reactions can lead to serious morbidity and mortality. Pharmacogenetic (PGx) testing can predict responses to medications and increased risks of adverse events where the genetic basis is understood. Several published manuscripts suggest positive impacts of systematic preemptive PGx testing. However, few studies have been conducted on PGx implementation in the Military Health System (MHS).
Material and methods:
A cross-sectional study of adult beneficiaries in a primary care clinic at a large military treatment facility was conducted in 2022. Participants underwent PGx genotyping of CYP2C19 and CYP2D6 genes at the Defense Health Agency Genetics Reference Laboratory. Participant medication lists were compared to the current Clinical Pharmacogenetic Implementation Consortium (CPIC) PGx gene-drug guidelines to assess potential actionability of these results.
Results:
Genotyping of CYP2C19 and CYP2D6 in 165 MHS beneficiaries (mean age: 65 years) revealed that 81.2% of participants had at least one abnormal PGx finding. Among those with an abnormal PGx result, 65% were taking a medication listed on the CPIC website with an association with the particular gene in which the finding was identified. In addition, 78% of all of the participants in the study were taking at least one medication that is metabolized by CYP2C19 or CYP2D6 with associated CPIC guidelines.
Conclusions:
Pharmacogenetic testing for CYP2C19 and CYP2D6 identified a substantial proportion of MHS patients at a single center who could benefit from evaluation of current medication regimens based on the CPIC guidelines. Individualized medical management may be warranted to a greater degree than previously recognized based on the findings given possible differences in medication metabolism. Many MHS beneficiaries already take medications metabolized by CYP2C19 and CYP2D6, and a substantial proportion may be at risk for preventable adverse events for medications metabolized by these enzymes. While preliminary, a large number of actionable polymorphisms among a relatively small set of individuals taking at-risk medications suggest that implementing PGx testing in clinical practice may be beneficial in the MHS with appropriate clinical infrastructure.
Objective. The aim of this exploratory study was to ascertain the current educational status of pharmacogenomics (PGx) within the present and future UK pharmacy profession, in addition to ascertaining future educational and infrastructure needs of pharmacists to adopt PGx into practice. Methods. A 35-question survey was sent electronically to practicing pharmacists, preregistration pharmacists, and Master of Pharmacy (MPharm) students throughout the UK between April 2018 and May 2019. Responses were anonymous and analysed using GraphPad Prism 8 and SPSS statistics 26. Results. In total, 264 participants, where data could be used for analysis, responded to the survey. This comprised 196 practicing pharmacists and 68 preregistration pharmacists/MPharm students. The findings demonstrated variation in undergraduate level exposure to PGx between those who had qualified within the past 10 years and those who had qualified over 10 years ago. Over 60% of qualified pharmacists did not feel confident in identifying drugs that require PGx testing. Nearly three quarters of respondents cited that PGx guidelines were needed to help facilitate a PGx service, although 63.6% also stated that they had previously never looked for a PGx recommendation. Most respondents cited PGx as a low or medium learning priority. Conclusion. Our survey suggests that further education is required to prepare the UK pharmacy workforce for the advent of PGx. A focus on the provision of, and education around, PGx guidelines is needed. In addition, the disparity identified between pharmacists at different stages of their career will need to be addressed with tailored and targeted educational packages.
Aim:
To investigate whether it is feasible to perform PGx testing and implement the test results as part of medication reviews during hospitalisation of multimorbid patients.
Methods:
Patients with ≥ 2 chronic conditions and ≥ 5 regular drugs with at least one potential gene-drug interaction (GDI) were included from one geriatric and one cardiology ward for pharmacogenetic testing. After inclusion by the study pharmacist, blood samples were collected and shipped to the laboratory for analysis. For patients still hospitalised at the time when the pharmacogenetic test results were available, the information was used in medication reviews. Recommendations from the pharmacist on actionable GDIs were communicated to the hospital physicians, who subsequently decided on potential immediate changes or forwarded suggestions in referrals to general practitioners.
Results:
The pharmacogenetic test results were available for medication review in 18 of the 46 patients (39.1 %), where median length of hospital stay was 4.7 days (1.6-18.3). The pharmacist recommended medication changes for 21 of 49 the detected GDIs (42.9%). The hospital physicians accepted 19 (90.5 %) of the recommendations. The most commonly detected GDIs involved metoprolol (CYP2D6 genotype), clopidogrel (CYP2C19 genotype), and atorvastatin (CYP3A4/5 and SLCOB1B1 genotype).
Conclusions:
The study shows that implementation of pharmacogenetic testing for medication review of hospitalised patients have the potential of improving drug treatment before being transferred to primary care. However, the logistics workflow needs to be further optimised, as test results were available during hospitalisation for less than half of the patients included in the study.
Aim: To assess knowledge, confidence and perceptions of healthcare professionals specializing in primary care and pain management at Brigham and Women's Hospital, related to clinical pharmacogenomics (PGx). Methods: A 25-question online survey was distributed to 328 Brigham and Women's Hospital clinicians for analysis. Results: Thirty-four clinicians completed the survey. Respondents had minimal experience with PGx and limited awareness of PGx resources. Although respondents expressed belief that PGx has utility to improve medication-related patient outcomes, many lack confidence to apply PGx results to their practice. For clinical drug-gene questions relevant to primary care and/or pain management, respondents scored poorly. Conclusion: More clinician education is needed for appropriate utilization of PGx in clinical practice as it pertains to primary care and pain management.
Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.
Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests’ reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.
Using pharmacogenetics (PGx) to inform clinical decision making can benefit patients but clinical use of PGx testing has been limited. Existing genetics data obtained in the course of research could be used to identify patients who are suspected, but have not yet been confirmed, to carry clinically actionable genotypes, in whom confirmatory genetic testing could be conducted for highly efficient PGx implementation. Herein we demonstrate that it is regulatorily and technically feasible to implement PGx by identifying suspected carriers of actionable genotypes within an institutional genetics data repository and conduct confirmatory PGx testing immediately prior to that patient receiving the PGx-relevant drug, using a case study of DPYD testing prior to fluoropyrimidine chemotherapy. In two years since launching this program, ~3,000 suspected DPYD carriers have been passively monitored and one confirmed DPYD carrier was prevented from receiving unacceptably toxic fluoropyrimidine treatment, for minimal cost and effort. Now that we have demonstrated the feasibility of this strategy, we plan to transition to PGx panel testing and expand implementation to other genes and drugs for which the evidence of clinical benefit of PGx-informed treatment is high but PGx testing is not generally conducted. This highly efficient implementation process will maximize the clinical benefits of testing and could be explored at other institutions that have research-only genetic data repositories to expand the number of patients who benefit from PGx-informed treatment while we continue to work toward wide-scale adoption of PGx testing and implementation.
The practice of precision medicine considers a variety of sources of information to optimize patient care. Factors such as patient demographics, clinical history, and lab test values have well understood effects on treatment outcomes and influence decision making. However, effective inclusion of biomolecular data such as protein expression and DNA sequencing data within the practice of precision medicine needs continued study. Informatics tools offer solutions to allow these complex data sources to be effectively embraced. Utilization of informatics tools to visualize data pertaining to the gene selection practices of pharmacogenomic (PGx) tests effectively communicated large amounts of information into concise heatmaps. After a thorough search identifying potential PGx tests, their detection rates were assessed based on their gene targets and the genomic frequencies of various ethnic groups. Detection rates were defined as the proportion of a prospective ethnic population where PGx tests selected both variants within genotypes of requiring alterations in medication therapy. Detection rates had high levels of variance between different assays and ethnic groups. Our results strongly support the practice of clinicians considering a patient’s ethnic background when selecting a PGx test that is right for them to ensure effective testing. In addition to genetic test selection, applied informatics tools allow for better utilization of biomolecular information in patient prognosis assessment and therapy selection. We demonstrated this on a cohort on non-small cell lung cancer patients receiving immune checkpoint inhibitor (ICI) therapy. Through multivariate statistical models and vi survival analyses, we demonstrated the impact of various clinical and biomolecular variables on patient survival. Our results showed patients experiencing immune related adverse events (irAEs) and their timing had a significant impact on patient survival time. Additionally, we demonstrated the timing of genotype targeted tyrosine kinase inhibitor therapy relative to ICI therapy has a significant impact on patient survival time as well. Variables with less understood associations with patient survival were effectively contextualized with common clinical variables within multivariate modeling approaches. Continued implementation of informatics approaches is vital to effectively embrace a precision medicine approach in patient care.
Objectives Integrating genetic test results into the electronic health record (EHR) is essential for integrating genetic testing into clinical practice. This article describes the organizational challenges of integrating discrete apolipoprotein L1 (APOL1) genetic test results into the EHR for a research study on culturally sensitive genetic counseling for living kidney donors.
Methods We convened a multidisciplinary team across three institutions (Northwestern University, Northwestern Memorial HealthCare [NMHC], and OHSU Knight Diagnostic Laboratories [KDL]), including researchers, physicians, clinical information technology, and project management. Through a series of meetings over a year between the team and the genetic testing laboratory, we explored and adjusted our EHR integration plan based on regulatory and budgetary constraints.
Results Our original proposal was to transmit results from KDL to NMHC as structured data sent via Health Level Seven (HL7) v2 message. This was ultimately deemed infeasible given the time and resources required to establish the interface, and the low number of samples to be processed for the study (n = 316). We next explored the use of Epic's Care Everywhere interoperability platform, but learned it was not possible as a laboratory test ordered for a research study; even though our intent was to study the APOL1 genetic test result's clinical use and impact, test results were still considered “research results.” Faced with two remaining options—downloading a PDF from the KDL laboratory portal or scanning a faxed result from KDL—only a PDF of the APOL1 test result could be integrated into the EHR, reinforcing the status quo.
Conclusion Even with early and ongoing stakeholder engagement, dedicated project management, and funding, unanticipated implementation challenges—especially for research projects—can result in drastic design tradeoffs.
Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.Key wordsPharmacogenomicsStatistical genomicsRare variantsHigh-throughput sequencingHaplotypesQuality control
Whole genome sequencing (WGS) is rapidly approaching widespread clinical application. Technology advancements over the past decade, since the first human genome was decoded, have made it feasible to use WGS for clinical care. Future advancements will likely drive down the price to the point wherein WGS is routinely available for care. However, were this to happen today, most of the genetic information available to guide clinical care would go unused due to the complexity of genetics, limited physician proficiency in genetics, and lack of genetics professionals in the clinical workforce. Furthermore, these limitations are unlikely to change in the future. As such, the use of clinical decision support (CDS) to guide genome-guided clinical decision-making is imperative. In this manuscript, we describe the barriers to widespread clinical application of WGS information, describe how CDS can be an important tool for overcoming these barriers, and provide clinical examples of how genome-enabled CDS can be used in the clinical setting.
Codeine is bioactivated to morphine, a strong opioid agonist, by the hepatic cytochrome P450 2D6 (CYP2D6); hence, the efficacy and safety of codeine are governed by CYP2D6 activity. Polymorphisms are a major cause of CYP2D6 variability. We summarize evidence from the literature supporting this association and provide therapeutic recommendations for codeine based on CYP2D6 genotype. This document is an update to the 2012 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for CYP2D6 genotype and codeine therapy.
Glucose-6-phosphate dehydrogenase (G6PD) deficiency is associated with development of acute hemolytic anemia (AHA) induced by a number of drugs. We provide guidance as to which G6PD genotypes are associated with G6PD deficiency in males and females. Rasburicase is contraindicated in G6PD deficient patients due to the risk of AHA and possibly methemoglobinemia. Unless preemptive genotyping has established a positive diagnosis of G6PD deficiency, quantitative enzyme assay remains the mainstay of screening prior to rasburicase.Clinical Pharmacology & Therapeutics (2014); Accepted article preview online 02 May 2014 doi:10.1038/clpt.2014.97.
The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help
clinicians understand how available genetic test results could be used to optimize drug therapy. CPIC has focused initially on well-known
examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC
guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes
and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help
clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the
development process of the CPIC guidelines and compares this process to the Institute of Medicine’s Standards for Developing Trustworthy
Clinical Practice Guidelines.
Pharmacogenetics (PG) examines gene variations for drug disposition, response, or toxicity. At the National Institutes of Health Clinical Center (NIH CC), a multidepartment Pharmacogenetics Testing Implementation Committee (PGTIC) was established to develop clinical decision support (CDS) algorithms for abacavir, carbamazepine, and allopurinol, medications for which human leukocyte antigen (HLA) variants predict severe hypersensitivity reactions. Providing PG CDS in the electronic health record (EHR) during order entry could prevent adverse drug events. Medical Logic Module (MLM) programming was used to implement PG CDS in our EHR. The MLM checks to see if an HLA sequence-based gene test is ordered. A message regarding test status (result present, absent, pending, or test not ordered) is displayed on the order form, and the MLM determines if the prescriber can place the order, place it but require an over-ride reason, or be blocked from placing the order. Since implementation, more than 725 medication orders have been placed for over 230 patients by 154 different prescribers for the three drugs included in our PG program. Prescribers commonly used an over-ride reason when placing the order mainly because patients had been receiving the drug without reaction before implementation of the CDS program. Successful incorporation of PG CDS into the NIH CC EHR required a coordinated, interdisciplinary effort to ensure smooth activation and a positive effect on patient care. Prescribers have adapted to using the CDS and have ordered PG testing as a direct result of the implementation.
PEG-interferon-α and ribavirin based regimens are the mainstay for treatment of Hepatitis C Virus (HCV) genotype 1. IFNL3 (IL28B) genotype is the strongest baseline predictor of response to PEG-interferon-α and ribavirin therapy in previously untreated patients and can be used by patients and clinicians as part of shared decision making process for initiating treatment for HCV infection. We provide information regarding the clinical use of PEG-interferon-α and ribavirin containing regimens based on IFNL3 genotype.Clinical Pharmacology & Therapeutics (2013); accepted article preview online 4 October 2013 doi:10.1038/clpt.2013.203.
Clinical decision support embedded into clinical information systems, such as electronic health records, is recognized as necessary to facilitate the appropriate use of genomic information. There are many lessons learned from more than five decades of experience in CDS implementation that can guide us during the genomic era. We provide an overview of existing frameworks for evaluating health IT infrastructures for CDS; processes for genetic testing and data access; and rationale for the Electronic Medical Records & Genomics (eMERGE) Network work on establishing a common ground for discussing CDS solutions among heterogeneous IT infrastructures. We provide examples from the eMERGE Network that can characterize genomic CDS using frameworks from the pre-genomic CDS era and outline lessons from implementing pre-genomic CDS that can account for variation in health IT infrastructures. Finally, we propose a framework to describe opportunities for genomic CDS, that supports provider and consumer-initiated genetic testing and data access.
The fluoropyrimidines are the mainstay chemotherapeutic agents for the treatment of many types of cancers. Detoxifying metabolism of fluoropyrimidines requires dihydropyrimidine dehydrogenase (DPD encoded by the DPYD gene) and reduced or absent activity of this enzyme can result in severe and sometimes fatal toxicity. We summarize evidence from the published literature supporting this association and provide dosing recommendations for fluoropyrimidines based on DPYD genotype (updates at www.pharmgkb.org).Clinical Pharmacology & Therapeutics (2013); accepted article preview online 29 August 2013; doi:10.1038/clpt.2013.172.
Active clinical decision support (CDS) delivered through an electronic health record (EHR) facilitates gene-based drug prescribing and other applications of genomics to patient care.
We describe the development, implementation, and evaluation of active CDS for multiple pharmacogenetic test results reported preemptively.
Clinical pharmacogenetic test results accompanied by clinical interpretations are placed into the patient's EHR, typically before a relevant drug is prescribed. Problem list entries created for high-risk phenotypes provide an unambiguous trigger for delivery of post-test alerts to clinicians when high-risk drugs are prescribed. In addition, pre-test alerts are issued if a very-high risk medication is prescribed (eg, a thiopurine), prior to the appropriate pharmacogenetic test result being entered into the EHR. Our CDS can be readily modified to incorporate new genes or high-risk drugs as they emerge.
Through November 2012, 35 customized pharmacogenetic rules have been implemented, including rules for TPMT with azathioprine, thioguanine, and mercaptopurine, and for CYP2D6 with codeine, tramadol, amitriptyline, fluoxetine, and paroxetine. Between May 2011 and November 2012, the pre-test alerts were electronically issued 1106 times (76 for thiopurines and 1030 for drugs metabolized by CYP2D6), and the post-test alerts were issued 1552 times (1521 for TPMT and 31 for CYP2D6). Analysis of alert outcomes revealed that the interruptive CDS appropriately guided prescribing in 95% of patients for whom they were issued.
Our experience illustrates the feasibility of developing computational systems that provide clinicians with actionable alerts for gene-based drug prescribing at the point of care.
In clinical exome and genome sequencing, there is a potential for the recognition and reporting of incidental or secondary findings unrelated to the indication for ordering the sequencing but of medical value for patient care. The American College of Medical Genetics and Genomics (ACMG) recently published a policy statement on clinical sequencing that emphasized the importance of alerting the patient to the possibility of such results in pretest patient discussions, clinical testing, and reporting of results. The ACMG appointed a Working Group on Incidental Findings in Clinical Exome and Genome Sequencing to make recommendations about responsible management of incidental findings when patients undergo exome or genome sequencing. This Working Group conducted a year-long consensus process, including an open forum at the 2012 Annual Meeting and review by outside experts, and produced recommendations that have been approved by the ACMG Board. Specific and detailed recommendations, and the background and rationale for these recommendations, are described herein. The ACMG recommends that laboratories performing clinical sequencing seek and report mutations of the specified classes or types in the genes listed here. This evaluation and reporting should be performed for all clinical germline (constitutional) exome and genome sequencing, including the “normal” of tumor-normal subtractive analyses in all subjects, irrespective of age but excluding fetal samples. We recognize that there are insufficient data on penetrance and clinical utility to fully support these recommendations, and we encourage the creation of an ongoing process for updating these recommendations at least annually as further data are collected.
Genet Med 2013:15(7):565–574
Cytochrome P450 (CYP)2C19 catalyzes the bioactivation of the antiplatelet prodrug clopidogrel, and CYP2C19 loss-of-function alleles impair formation of active metabolites, resulting in reduced platelet inhibition. In addition, CYP2C19 loss-of-function alleles confer increased risks for serious adverse cardiovascular (CV) events among clopidogrel-treated patients with acute coronary syndromes (ACSs) undergoing percutaneous coronary intervention (PCI). Guideline updates include emphasis on appropriate indication for CYP2C19 genotype–directed antiplatelet therapy, refined recommendations for specific CYP2C19 alleles, and additional evidence from an expanded literature review (updates at http://www.pharmgkb.org).
Human leukocyte antigen B (HLA-B) is a gene that encodes a cell surface protein involved in presenting antigens to the immune system. The variant allele HLA-B*15:02 is associated with an increased risk of Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in response to carbamazepine treatment. We summarize evidence from the published literature supporting this association and provide recommendations for the use of carbamazepine based on HLA-B genotype (also available on PharmGKB: http://www.pharmgkb.org). The purpose of this article is to provide information to allow the interpretation of clinical HLA-B*15:02 genotype tests so that the results can be used to guide the use of carbamazepine. The guideline provides recommendations for the use of carbamazepine when HLA-B*15:02 genotype results are available. Detailed guidelines regarding the selection of alternative therapies, the use of phenotypic tests, when to conduct genotype testing, and cost-effectiveness analyses are beyond the scope of this document. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines are published and updated periodically on the PharmGKB website at (http://www.pharmgkb.org).
The pace of discovery of potentially actionable pharmacogenetic variants has increased dramatically in recent years. However, the implementation of this new knowledge for individualized patient care has been slow. The Pharmacogenomics Research Network (PGRN) Translational Pharmacogenetics Program seeks to identify barriers and develop real-world solutions to implementation of evidence-based pharmacogenetic tests in diverse health-care settings. Dissemination of the resulting toolbox of "implementation best practices" will prove useful to a broad audience.
Polymorphisms in CYP2D6 and CYP2C19 affect the efficacy and safety of tricyclics, with some drugs being affected by CYP2D6 only, and others by both polymorphic enzymes. Amitriptyline, clomipramine, doxepin, imipramine, and trimipramine are demethylated by CYP2C19 to pharmacologically active metabolites. These drugs and their metabolites, along with desipramine and nortriptyline, undergo hydroxylation by CYP2D6 to less active metabolites. Evidence from published literature is presented for CYP2D6 and CYP2C19 genotype-directed dosing of tricyclic antidepressants.Clinical Pharmacology & Therapeutics (2013); advance online publication 13 March 2013. doi:10.1038/clpt.2013.2.
The Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Thiopurine Methyltransferase Genotype and Thiopurine Dosing was originally published in March 2011. We reviewed recent literature and concluded that although relevant new evidence has been generated, none of the evidence would change the primary dosing recommendations in the original guideline; therefore, the original publication remains clinically current. Up-to-date information on thiopurine methyltransferase (TPMT) gene alleles and nomenclature can be found at PharmGKB (http://www.pharmgkb.org).Clinical Pharmacology & Therapeutics (2013); 93 4, 324-325. doi:10.1038/clpt.2013.4
The National Institutes of Health Genetic Testing Registry (GTR; available online at http://www.ncbi.nlm.nih.gov/gtr/) maintains comprehensive information about testing offered worldwide for disorders with a genetic basis. Information is voluntarily
submitted by test providers. The database provides details of each test (e.g. its purpose, target populations, methods, what
it measures, analytical validity, clinical validity, clinical utility, ordering information) and laboratory (e.g. location,
contact information, certifications and licenses). Each test is assigned a stable identifier of the format GTR000000000, which
is versioned when the submitter updates information. Data submitted by test providers are integrated with basic information
maintained in National Center for Biotechnology Information’s databases and presented on the web and through FTP (ftp.ncbi.nih.gov/pub/GTR/_README.html).
Initiation of warfarin therapy using trial-and-error dosing is problematic. Our goal was to develop and validate a pharmacogenetic algorithm. In the derivation cohort of 1,015 participants, the independent predictors of therapeutic dose were: VKORC1 polymorphism -1639/3673 G>A (-28% per allele), body surface area (BSA) (+11% per 0.25 m2), CYP2C9*3 (-33% per allele), CYP2C9*2 (-19% per allele), age (-7% per decade), target international normalized ratio (INR) (+11% per 0.5 unit increase), amiodarone use (-22%), smoker status (+10%), race (-9%), and current thrombosis (+7%). This pharmacogenetic equation explained 53–54% of the variability in the warfarin dose in the derivation and validation (N= 292) cohorts. For comparison, a clinical equation explained only 17–22% of the dose variability (P < 0.001). In the validation cohort, we prospectively used the pharmacogenetic-dosing algorithm in patients initiating warfarin therapy, two of whom had a major hemorrhage. To facilitate use of these pharmacogenetic and clinical algorithms, we developed a nonprofit website, http://www.WarfarinDosing.org.
Well-characterized genes that affect warfarin metabolism (cytochrome P450 (CYP) 2C9) and sensitivity (vitamin K epoxide reductase complex 1 (VKORC1)) explain one-third of the variability in therapeutic dose before the international normalized ratio (INR) is measured. To determine genotypic relevance after INR becomes available, we derived clinical and pharmacogenetic refinement algorithms on the basis of INR values (on day 4 or 5 of therapy), clinical factors, and genotype. After adjusting for INR, CYP2C9 and VKORC1 genotypes remained significant predictors (P < 0.001) of warfarin dose. The clinical algorithm had an R2 of 48% (median absolute error (MAE): 7.0 mg/week) and the pharmacogenetic algorithm had an R2 of 63% (MAE: 5.5 mg/week) in the derivation set (N = 969). In independent validation sets, the R2 was 26–43% with the clinical algorithm and 42–58% when genotype was added (P = 0.002). After several days of therapy, a pharmacogenetic algorithm estimates the therapeutic warfarin dose more accurately than one using clinical factors and INR response alone.
Advances in pharmacogenetic testing will expand the number of clinically important pharmacogenetic variants. Communication and interpretation of these test results are critical steps in implementation of pharmacogenetics into the clinic. Computational tools that integrate directly into the electronic medical record (EMR) are needed to translate the growing number of genetic variants into interpretive consultations to facilitate gene-based drug prescribing. Herein, we describe processes for incorporating pharmacogenetic tests and interpretations into the EMR for clinical practice.Clinical Pharmacology & Therapeutics (2012); advance online publication 19 September 2012. doi:10.1038/clpt.2012.140.
Research on genes and medications has advanced our understanding of the genetic basis of individual drug responses. The aim of pharmacogenomics is to develop strategies for individualizing therapy for patients, in order to optimize outcome through knowledge of the variability of the human genome and its influence on drug response. Pharmacogenomics research is translational in nature and ranges from discovery of genotype-phenotype relationships to clinical trials that can provide proof of clinical impact. Advances in pharmacogenomics offer significant potential for subsequent clinical application in individual patients; however, the translation of pharmacogenomics research findings into clinical practice has been slow. Key components to successful clinical implementation of pharmacogenomics will include consistent interpretation of pharmacogenomics test results, availability of clinical guidelines for prescribing on the basis of test results, and knowledge-based decision support systems.
There are several hurdles to the clinical implementation of pharmacogenetics. One approach is to employ pre-prescription genotyping, involving interrogation of multiple pharmacogenetic variants using a high-throughput platform. We compared the performance of the Drug Metabolizing Enzymes and Transporters (DMET) Plus array (1,931 variants in 225 genes) with that of orthogonal genotyping methods in 220 pediatric patients. A total of 1,692 variants had call rates >98% and were in Hardy-Weinberg equilibrium. Of these, 259 were genotyped by at least one independent method, and a total of 19,942 single-nucleotide polymorphism (SNP)-patient sample pairs were evaluated. The concordance rate was 99.9%, with only 28 genotype discordances observed. For the genes deemed most likely to be clinically relevant (TPMT, CYP2D6, CYP2C19, CYP2C9, VKORC1, DPYD, UGT1A1, and SLCO1B1), a total of 3,799 SNP-patient sample pairs were evaluable and had a concordance rate of 99.96%. We conclude that the DMET Plus array performs well with primary patient samples, with the results in good concordance with those of several lower-throughput genotyping methods.
Routine integration of genotype data into drug decision making could improve patient safety, particularly if many relevant genetic variants can be assayed simultaneously before prescribing the target drug. The frequency of opportunities for pharmacogenetic prescribing and the potential adverse events (AEs) mitigated are unknown. We examined the frequency with which 56 medications with known outcomes influenced by variant alleles were prescribed in a cohort of 52,942 medical home patients at Vanderbilt University Medical Center (VUMC). Within a 5-year window, we estimated that 64.8% (95% confidence interval (CI): 64.4-65.2%) of individuals were exposed to at least one medication with an established pharmacogenetic association. Using previously published results for six medications with severe, well-characterized, genetically linked AEs, we estimated that 383 events (95% CI, 212-552) could have been prevented with an effective preemptive genotyping program. Our results suggest that multiplexed, preemptive genotyping may represent an efficient alternative approach to current single-use ("reactive") methods and may also improve safety.
Cholesterol reduction from statin therapy has been one of the greatest public health successes in modern medicine. Simvastatin is among the most commonly used prescription medications. A non-synonymous coding single-nucleotide polymorphism (SNP), rs4149056, in SLCO1B1 markedly increases systemic exposure to simvastatin and the risk of muscle toxicity. This guideline explores the relationship between rs4149056 (c.521T>C, p.V174A) and clinical outcome for all statins. The strength of the evidence is high for myopathy with simvastatin. We limit our recommendations accordingly.
The promise of "personalized medicine" guided by an understanding of each individual's genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant information. We describe the operational implementation of prospective genotyping linked to an advanced clinical decision-support system to guide individualized health care in a large academic health center. This approach to personalized medicine entails engagement between patient and health-care provider, identification of relevant genetic variations for implementation, assay reliability, point-of-care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most of whom were scheduled for cardiac catheterization, were genotyped on a multiplexed platform that included genotyping for CYP2C19 variants that modulate response to the widely used antiplatelet drug clopidogrel. These data are deposited into the electronic medical record (EMR), and point-of-care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.
Background Genetic variability among patients plays an important role in determining the dose of warfarin that should be used when oral anticoagulation is initiated, but practical methods of using genetic information have not been evaluated in a diverse and large population. We developed and used an algorithm for estimating the appropriate warfarin dose that is based on both clinical and genetic data from a broad population base. Methods Clinical and genetic data from 4043 patients were used to create a dose algorithm that was based on clinical variables only and an algorithm in which genetic information was added to the clinical variables. In a validation cohort of 1009 subjects, we evaluated the potential clinical value of each algorithm by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable therapeutic dose; we also evaluated other clinically relevant indicators. Results In the validation cohort, the pharmacogenetic algorithm accurately identified larger proportions of patients who required 21 mg of warfarin or less per week and of those who required 49 mg or more per week to achieve the target international normalized ratio than did the clinical algorithm ( 49.4% vs. 33.3%, P< 0.001, among patients requiring <= 21 mg per week; and 24.8% vs. 7.2%, P< 0.001, among those requiring >= 49 mg per week). Conclusions The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed- dose approach. The greatest benefits were observed in the 46.2% of the population that required 21 mg or less of warfarin per week or 49 mg or more per week for therapeutic anticoagulation.
Human leukocyte antigen B (HLA-B) is responsible for presenting peptides to immune cells and plays a critical role in normal immune recognition of pathogens. A variant allele, HLA-B*57:01, is associated with increased risk of a hypersensitivity reaction to the anti-HIV drug abacavir. In the absence of genetic prescreening, hypersensitivity affects ~6% of patients and can be life-threatening with repeated dosing. We provide recommendations (updated periodically at http://www.pharmkgb.org) for the use of abacavir based on HLA-B genotype.
Codeine is bioactivated to morphine, a strong opioid agonist, by the hepatic cytochrome P450 2D6 (CYP2D6); hence, the efficacy and safety of codeine as an analgesic are governed by CYP2D6 polymorphisms. Codeine has little therapeutic effect in patients who are CYP2D6 poor metabolizers, whereas the risk of morphine toxicity is higher in ultrarapid metabolizers. The purpose of this guideline (periodically updated at http://www.pharmgkb.org) is to provide information relating to the interpretation of CYP2D6 genotype test results to guide the dosing of codeine.
Summary of recommendations:
The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group found that the evidence is currently insufficient to recommend for or against the routine use of UGT1A1 genotyping in patients with metastatic colorectal cancer who are to be treated with irinotecan, with the intent of modifying the dose as a way to avoid adverse drug reactions (severe neutropenia).
Rationale:
The EGAPP Working Group (EWG) found no intervention trials showing that targeted dosing of irinotecan based on UGT1A1 genotyping could reduce the rates of two specific adverse drug events, severe (Grade 3-4) neutropenia or diarrhea. Observational studies indicate a significant association between UGT1A1 genotypes, particularly *28/*28 and *1/*28, and the occurrence of severe neutropenia. Observational studies also indicate a possible association between severe diarrhea and these UGT1A1 genotypes, but the association is not statistically significant. An additional finding was the suggestion that reducing irinotecan dose may result in patient harms due to diminished effectiveness of treatment in highest risk individuals (*28/*28 homozygotes), and that a higher dose might be warranted among individuals at lower risk of adverse drug events (*1/*1 and *1/*28 genotypes). This review did not consider higher risk patients (e.g., having previous adverse reactions to irinotecan or additional risk factors for neutropenia).
Analytic validity:
The EWG found adequate evidence to conclude that analytic sensitivity and specificity were high for the commonly tested alleles, but evidence was inadequate for rarer alleles.
Clinical validity:
The EWG found adequate evidence of a significant association between UGT1A1 genotype and the incidence of severe neutropenia at standard doses of irinotecan. The EWG found adequate evidence of a possible association between genotype and severe diarrhea, but the effect was smaller and not statistically significant. The EWG found adequate evidence of a significantly higher rate of tumor response to standard irinotecan dosing among individuals with the genotype at highest risk of adverse drug events (*28/*28).
Clinical utility:
The EWG found no evidence to support clinical utility in the proposed clinical scenario. Preliminary modeling suggests that, even if targeted dosing were to be highly effective, it is not clear that benefits (reduced adverse drug events) outweigh harms (unresponsive tumors).
Contextual issues:
Addressing patient preferences regarding risk of side effects and quality of life, versus aggressive treatment to potentially improve effectiveness, is expected practice. In addition, a recent study reported that risk for neutropenia was lower at lower irinotecan doses. For treatment regimens utilizing lower irinotecan doses, UGT1A1 genotype may not be a useful indicator of risk for adverse drug events. Further rigorous evaluation of UGT1A1 genotyping using current and promising irinotecan treatment protocols is warranted.
Pharmacogenetics is frequently cited as an area for initial focus of the clinical implementation of genomics. Through the PG4KDS protocol, St. Jude Children's Research Hospital pre-emptively genotypes patients for 230 genes using the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array supplemented with a CYP2D6 copy number assay. The PG4KDS protocol provides a rational, stepwise process for implementing gene/drug pairs, organizing data, and obtaining consent from patients and families. Through August 2013, 1,559 patients have been enrolled, and four gene tests have been released into the electronic health record (EHR) for clinical implementation: TPMT, CYP2D6, SLCO1B1, and CYP2C19. These genes are coupled to 12 high-risk drugs. Of the 1,016 patients with genotype test results available, 78% of them had at least one high-risk (i.e., actionable) genotype result placed in their EHR. Each diplotype result released to the EHR is coupled with an interpretive consult that is created in a concise, standardized format. To support-gene based prescribing at the point of care, 55 interruptive clinical decision support (CDS) alerts were developed. Patients are informed of their genotyping result and its relevance to their medication use through a letter. Key elements necessary for our successful implementation have included strong institutional support, a knowledgeable clinical laboratory, a process to manage any incidental findings, a strategy to educate clinicians and patients, a process to return results, and extensive use of informatics, especially CDS. Our approach to pre-emptive clinical pharmacogenetics has proven feasible, clinically useful, and scalable. © 2014 Wiley Periodicals, Inc.
To report the design and implementation of the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment protocol that was developed to test the concept that prescribers can deliver genome-guided therapy at the point of care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated into the electronic medical record (EMR).
We used a multivariate prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among the Mayo Clinic Biobank participants, with a recruitment goal of 1000 patients. We used a Cox proportional hazards model with variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR.
The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for International Classification of Diseases, Ninth Revision codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 1013 (51%) provided blood samples, 256 (13%) declined participation, 555 (28%) did not respond, and 176 (9%) consented but did not provide a blood sample within the recruitment window (October 4, 2012, through March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS was integrated into the EMR and flagged potential patient-specific drug-gene interactions and provided therapeutic guidance.
This translational project provides an opportunity to begin to evaluate the impact of preemptive sequencing and EMR-driven genome-guided therapy. These interventions will improve understanding and implementation of genomic data in clinical practice.
Since September 2010, over 10,000 patients have undergone preemptive, panel-based pharmacogenomic testing through the Vanderbilt Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT) program. Analysis of the genetic data from the first 9,589 individuals reveals the frequency of genetic variants is concordant with published allele frequencies. Based on five currently implemented drug-genome interactions, the multiplexed test identified one or more actionable variants in 91% of the genotyped patients and in 96% of African-American patients. Using medication exposure data from electronic medical records, we compared a theoretical "reactive," prescription-triggered, serial single-gene testing strategy to our preemptive, multiplexed genotyping approach. Reactive genotyping would have generated 14,656 genetic tests. These data highlight three advantages of preemptive genotyping: 1)the vast majority of patients carry at least one pharmacogene variant; 2)data are available at the point of care; and 3)there is a substantial reduction in testing burden compared to a reactive strategy.Clinical Pharmacology & Therapeutics (2013); accepted article preview online 19 November 2013 doi:10.1038/clpt.2013.229.
netics and pharmacologic effects of medica-tions is determined by their importance for the activation or inactivation of drug sub-strates. The effects can be profound toxicity for medications that have a narrow therapeu-tic index and are inactivated by a polymor-phic enzyme (for example, mercaptopurine, azathioprine, thioguanine, and fluorouracil) (6) or reduced efficacy of medications that require activation by an enzyme exhibiting genetic polymorphism (such as codeine) (7). However, the overall pharmacologic ef-fects of medications are typically not mono-genic traits; rather, they are determined by the interplay of several genes encoding proteins involved in multiple pathways of drug metab-olism, disposition, and effects. The potential polygenic nature of drug response is illustrat-
Next-generation sequencing technologies have enabled the sequencing of an entire genome for less than $4,000. With access to all the genetic variation in an individual, our task will be to use this information to assess the genetic influences on drug efficacy, toxicity, and dosage.
Recent years have seen great advances in our understanding of genetic contributors to drug response. Drug discovery and development around targeted genetic (somatic) mutations has led to a number of new drugs with genetic indications, particularly for the treatment of cancers. Our knowledge of genetic contributors to variable drug response for existing drugs has also expanded dramatically, such that the evidence now supports clinical use of genetic data to guide treatment in some situations, and across a variety of therapeutic areas. Clinical implementation of pharmacogenetics has seen substantial growth in recent years and groups are working to identify the barriers and best practices for pharmacogenetic-guided treatment. The advances and challenges in these areas are described and predictions about future use of genetics in drug therapy are discussed.
Background:
The ADME Core Panel assays 184 variants across 34 pharmacogenes, many of which are difficult to accurately genotype with standard multiplexing methods.
Methods:
We genotyped 326 frequently medicated individuals of European descent in Vanderbilt's biorepository linked to de-identified electronic medical records, BioVU, on the ADME Core Panel to assess quality and performance of the assay. We compared quality control metrics and determined the extent of direct and indirect marker overlap between the ADME Core Panel and the Illumina Omni1-Quad.
Results:
We found the quality of the ADME Core Panel data to be high, with exceptions in select copy number variants and markers in certain genes (notably CYP2D6). Most of the common variants on the ADME panel are genotyped by the Omni1, but absent rare variants and copy number variants could not be accurately tagged by single markers.
Conclusion:
Our frequently medicated study population did not convincingly differ in allele frequency from reference populations, suggesting that heterogeneous clinical samples (with respect to medications) have similar allele frequency distributions in pharmacogenetics genes compared with reference populations.
The University of Florida and Shands Hospital recently launched a genomic medicine program focused on the clinical implementation of pharmacogenetics called the Personalized Medicine Program. We focus on a pre-emptive, chip-based genotyping approach that is cost effective, while providing experience that will be useful as genomic medicine moves towards genome sequence data for patients becoming available. The Personalized Medicine Program includes a regulatory body that is responsible for ensuring that evidence-based examples are moved to clinical implementation, and relies on clinical decision support tools to provide healthcare providers with guidance on use of the genetic information. The pilot implementation was with CYP2C19-clopidogrel and future plans include expansion to additional pharmacogenetic examples, along with aiding in implementation in other health systems across Florida.
Tricyclic antidepressant (TCA) clinical pharmacogenetic implementation guidelines for CYP2D6 and CYP2C19 genotypes highlight the importance of both genes. However, studies of the combined impact of the two genes are sparse, limiting the ability to make strong recommendations based on both genes. The warfarin pharmacogenetics literature highlights the strength of a multigenic approach for discovery and clinical implementation. For optimal impact and interpretation, investigators are encouraged to conduct studies in the context of previously well-defined pharmacogenetics markers.
The Mayo Clinic Center for Individualized Medicine (CIM) is designed to discover and integrate the latest in genomic, molecular, and clinical science into personalized care for patients across a multiple-site academic medical center. Despite a highly integrated structure, fully electronic medical record, and strong administrative support, achievement of this goal has had challenges. This article will describe the activities of the CIM, with emphasis on the strategy being used to clinically implement genomics.
The exponential rise in genomics research over the past decade has yielded a growing number of sequence variants associated with medication response that may have clinical utility. Despite existing barriers, attention is turning to strategies that integrate these data into clinical care. The CLIPMERGE PGx Program is establishing a best-practices infrastructure for the implementation of genome-informed prescribing using a biobank-derived clinical cohort, preemptive genetic testing, and real-time clinical decision support deployed through the electronic health record.Clinical Pharmacology & Therapeutics (2013); 94 2, 214-217. doi:10.1038/clpt.2013.72
The promise of genomic medicine has received great attention over the past decade, projecting how genomics will soon guide the prevention, diagnosis, and treatment of human diseases. However, this evolution has been slower than forecast, even where evidence is often strong (e.g., pharmacogenomics). Reasons include the requirement for institutional resources and the need for the will to push beyond barriers impeding health-care changes. Here, we illustrate how genomics has been deployed to advance the treatment of childhood leukemia.Clinical Pharmacology & Therapeutics (2013); advance online publication 6 March 2013. doi:10.1038/clpt.2013.9.
High-throughput genomic measurements initially emerged for research purposes but are now entering the clinic. The challenge for clinicians is to integrate imperfect genomic measurements with other information sources so as to estimate as closely as possible the probabilities of clinical events (diagnoses, treatment responses, prognoses). Population-based data provide a priori probabilities that can be combined with individual measurements to compute a posteriori estimates using Bayes' rule. Thus, the integration of population science with individual genomic measurements will enable the practice of personalized medicine.
Allopurinol is the most commonly used drug for the treatment of hyperuricemia and gout. However, allopurinol is also one of the most common causes of severe cutaneous adverse reactions (SCARs), which include drug hypersensitivity syndrome, Stevens-Johnson syndrome, and toxic epidermal necrolysis. A variant allele of the human leukocyte antigen (HLA)-B, HLA-B*58:01, associates strongly with allopurinol-induced SCAR. We have summarized the evidence from the published literature and developed peer-reviewed guidelines for allopurinol use based on HLA-B genotype.Clinical Pharmacology & Therapeutics (2013); 93 2, 153-158. doi:10.1038/clpt.2012.209
The paradigm of individualized drug therapy based on genetics is an ideal that is now potentially possible. However, translation of pharmacogenomics into practice has encountered barriers such as limited availability and the high cost of genetic testing, the delays involved, disagreements about interpretation of results, and even lack of understanding about pharmacogenomics in general. We describe our institutional pharmacogenomics-implementation project, "The 1200 Patients Project," a model designed to overcome these barriers and facilitate the availability of pharmacogenomic information for personalized prescribing.
Although there is increasing evidence to support the implementation of pharmacogenetics in certain clinical scenarios, the adoption of this approach has been limited. The advent of preemptive and inexpensive testing of critical pharmacogenetic variants may overcome barriers to adoption. We describe the design of a customized array built for the personalized-medicine programs of the University of Florida and Stanford University. We selected key variants for the array using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB), and we included variants in drug metabolism and transporter genes along with other pharmacogenetically important variants.
To develop a benchmark measure of US physicians' level of knowledge and extent of use of pharmacogenomic testing, we conducted an anonymous, cross-sectional, fax-based, national survey. Of 397,832 physicians receiving the survey questionnaire, 10,303 (3%) completed and returned it; the respondents were representative of the overall US physician population. The factors associated with the decision to test were evaluated using χ(2) and multivariate logistic regression. Overall, 97.6% of responding physicians agreed that genetic variations may influence drug response, but only 10.3% felt adequately informed about pharmacogenomic testing. Only 12.9% of physicians had ordered a test in the previous 6 months, and 26.4% anticipated ordering a test in the next 6 months. Early and future adopters of testing were more likely to have received training in pharmacogenomics, but only 29.0% of physicians overall had received any education in the field. Our findings highlight the need for more effective physician education on the clinical value, availability, and interpretation of pharmacogenomic tests.
In this paper, we examine the clinical and economic challenges that face developers of and payers for personalized drugs and companion diagnostics. We review and summarize clinical, regulatory and reimbursement issues with respect to eight, high profile personalized medicines and their companion diagnostics. Subsequently, we determine Medicare parts B and D reimbursement of the eight drugs from publicly available databases. Finally, we utilize surveys-each tailored to three key stakeholders; payers, drug and diagnostic developers, and pharmacogenomic expert analysts-to assess reimbursement of diagnostics, analyze the role that different kinds of evidence have in informing prescribing and reimbursement decisions, as well as the specific clinical, regulatory and economic challenges that confront pharmacogenomics as it moves forward. We found that Medicare beneficiary access to physician-administered (Medicare part B) drugs is relatively unfettered, with a fixed patient co-insurance percentage of 20%. More reimbursement restrictions are placed on self-administered (Medicare part D) drugs, which translates into higher and more variable cost sharing, more use of prior authorization and quantity limits. There is a lack of comprehensive reimbursement of companion diagnostics, even in cases in which the diagnostic is on the label and recommended or required by the Food and Drug Administration. Lack of evidence linking diagnostic tests to health outcomes has caused payers to be skeptical about the clinical usefulness of tests. Expert analysts foresee moderate growth in post-hoc development of companion diagnostics to personalize already approved drugs, and limited growth in the concurrent co-development of companion diagnostics and personalized medicines. Lack of clinically useful diagnostics as well as an evidence gap in terms of knowledge of drug and diagnostic clinical effectiveness appear to be hindering growth in personalized medicine. An increase in comparative effectiveness research may help to close the evidence gap.The Pharmacogenomics Journal advance online publication, 10 January 2012; doi:10.1038/tpj.2011.63.
Clinical genetic testing has grown substantially over the past 30 years as the causative mutations for Mendelian diseases have been identified, particularly aided in part by the recent advances in molecular-based technologies. Importantly, the adoption of new tests and testing strategies (e.g., diagnostic confirmation, prenatal testing, and population-based carrier screening) has often been met with caution and careful consideration before clinical implementation, which facilitates the appropriate use of new genetic tests. Although the field of pharmacogenetics was established in the 1950s, clinical testing for constitutional pharmacogenetic variants implicated in interindividual drug response variability has only recently become available to help clinicians guide pharmacotherapy, in part due to US Food and Drug Administration-mediated product insert revisions that include pharmacogenetic information for selected drugs. However, despite pharmacogenetic associations with adverse outcomes, physician uptake of clinical pharmacogenetic testing has been slow. Compared with testing for Mendelian diseases, pharmacogenetic testing for certain indications can have a lower positive predictive value, which is one reason for underutilization. A number of other barriers remain with implementing clinical pharmacogenetics, including clinical utility, professional education, and regulatory and reimbursement issues, among others. This review presents some of the current opportunities and challenges with implementing clinical pharmacogenetic testing.
Today, more than ever, basic science research provides significant opportunities to advance our understanding about the genetic basis of human disease. Close interactions among laboratory, computational, and clinical research communities will be crucial to ensure that genomic discoveries advance medical science and, ultimately, improve human health.