Clinical Pharmacogenetics Implementation Consortium (CPIC)

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ABSTRACT Pharmacogenomics is often cited as the subset of genomic research that is most amenable to uptake in clinical medicine. Over the last few years, leading institutions have begun using pharmacogenetic test results to guide prescribing in some clinical settings, but clinical implementation efforts have documented that rigorous guidelines are needed to optimally use pharmacogenetic test results. Recognizing this need, we formed the Clinical Pharmacogenetics Implementation Consortium (CPIC®) in 2009. The goal of CPIC is to provide resources needed to translate raw genetic test information into prescribing recommendations for specific gene/drug pairs. This is accomplished through the creation, curation, and dissemination of peer-reviewed, evidence-based, freely available clinical practice gene/drug guidelines. CPIC is the only NIH-supported group to focus on translation of pharmacogenomic variation into prescribing actions. We have two specific aims: Aim 1 is to create, curate, and update pharmacogenetic guidelines, and Aim 2 is to work with guideline users and other public genomic resources to coordinate efforts, disseminate CPIC content, and be responsive to the needs of the global genomics community. CPIC guidelines are published after standard peer review, and are simultaneously posted online allowing for real-time updates of guidelines as new information emerges. CPIC assigns gene/drug pairs to levels of actionability based on standardized criteria. CPIC investigators, working with internationally recognized experts in each content area, write clinical guidelines for those genes that are clearly actionable for at least one drug. Guidelines follow best practices, using a standardized format, grading for levels of evidence and strength of clinical recommendations, and adhering to authorship processes that are consistent with the Institute of Medicine best practices for clinical guidelines. Guidelines include tables of the genomic variants that define alleles, assign function to alleles, estimate allele frequency among major ancestry groups, translate diplotypes into phenotypes, provide prescribing actionability for phenotypes, and include example clinical decision support language. Considerable outreach efforts by CPIC will continue and have resulted in broad uptake and endorsement of CPIC guidelines. Content is organized to facilitate usage by the broad research and clinical community, including related public databases such as PharmGKB, ClinGen, ClinVar, and PharmVar.