Empey, Philip E.

Barriers to incorporating pharmacogenetics into routine clinical practice in the United States are well documented. Initial surveys by the Clinical Pharmacogenetics Implementation Consortium (CPIC) in 2009 and 2010 identified barriers across four key domains that have hindered the widespread adoption of clinical pharmacogenetic testing. These are presented verbatim as: (i) absence of a definition of the processes required to interpret genotype information and to translate genetic information into clinical actions; (ii) need for recommended drug/gene pairs to implement clinically now; (iii) clinician resistance to consider pharmacogenetic information at the bedside; and (iv) concerns about test costs and reimbursement. Over time, many of these challenges have been overcome, and clinical pharmacogenetic testing has subsequently reached broader implementation. Despite this progress, several barriers remain that block further adoption. This narrative review used authors' expertise and experience to identify and describe current barriers to pharmacogenetic implementation across seven domains in the United States: equity and inclusion; guidelines and supporting evidence; regulatory agency oversight; payer coverage and insurance; availability of quality pharmacogenetic tests; electronic health records; and provider and patient education. Within each domain, it revisits past successes and challenges and explores remaining barriers. We also propose solutions to address ongoing challenges across these domains, including further expansion of recommendations beyond pharmacogenetic‐specific guidelines, standards for designing clinical decision support tools, and broader pharmacogenetics education. Addressing these remaining obstacles directs work to enable broader adoption of clinical pharmacogenetic implementation to ultimately improve patient outcomes.

Abstract Pharmacogenomics (PGx) is focused on the relationship between an individual's genetic makeup and their response to medications, with the overarching aim of guiding prescribing decisions to improve drug efficacy and reduce adverse events. The PGx and genomic medicine communities have worked independently for over 2 decades, developing separate standards and terminology, making implementation of PGx across all areas of genomic medicine difficult. To address this issue, the Clinical Genome Resource (ClinGen) Pharmacogenomics Working Group (PGxWG) was established by the National Institutes of Health (NIH)-funded ClinGen to initially create frameworks for evaluating gene–drug response clinical validity and actionability aligned with the ClinGen frameworks for evaluating monogenic gene–disease relationships, and a framework for classifying germline PGx variants similar to the American College of Medical Genetics (ACMG) and Association of Molecular Pathology (AMP) system for interpretation of disease-causing variants. These frameworks will leverage decades of work from well-established PGx resources facilitating buy-in among PGx stakeholders. In this report, we describe the background and major activities of the ClinGen PGxWG, and how this initiative will facilitate the critical inclusion of PGx into the larger context of genomic medicine.

AbstractThe DPYD gene encodes dihydropyrimidine dehydrogenase, the rate‐limiting enzyme for the metabolism of fluoropyrimidines 5‐fluorouracil and capecitabine. Genetic variants in DPYD have been associated with altered enzyme activity, therefore accurate detection and interpretation is critical to predict metabolizer status for individualized fluoropyrimidine therapy. The most commonly observed deleterious variation is the causal variant linked to the previously described HapB3 haplotype, c.1129‐5923C>G (rs75017182) in intron 10, which introduces a cryptic splice site. A benign synonymous variant in exon 11, c.1236G>A (rs56038477) is also linked to HapB3 and is commonly used for testing. Previously, these single‐nucleotide polymorphisms (SNPs) have been reported to be in perfect linkage disequilibrium (LD); therefore, c.1236G>A is often utilized as a proxy for the function‐altering intronic variant. Clinical genotyping of DPYD identified a patient who had c.1236G>A, but not c.1129‐5923C>G, suggesting that these two SNPs may not be in perfect LD, as previously assumed. Additional individuals with c.1236G>A, but not c.1129‐5923C>G, were identified in the Children's Mercy Data Warehouse and the All of Us Research Program version 7 cohort substantiating incomplete SNP linkage. Consequently, testing only c.1236G>A can generate false‐positive results in some cases and lead to suboptimal dosing that may negatively impact patient therapy and prospect of survival. Our data show that DPYD genotyping should include the functional variant c.1129‐5923C>G, and not the c.1236G>A proxy, to accurately predict DPD activity.