An active area of genomic medicine implementation at many health care organizations and academic medical centers includes development of decision support and return of results around pharmacogenomics. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has established guidelines surrounding gene-drug pairs that can and should lead to treatment modifications based on genetic variants. One of the challenges in implementing pharmacogenomics is the representation of the information in the CPIC guidelines (including star-alleles) and extracting these variants and haplotypes from genetic datasets. In a collaboration between the PGRN Statistical Analysis Resource (P-STAR), the Pharmacogenomics Knowledgebase (PharmGKB), the Clinical Genome Resource (ClinGen), and CPIC, we are developing a software tool to extract all CPIC guideline gene variants from a genetic dataset (represented as a vcf), interpret the variant alleles, and generate a report. The CPIC pipeline report can then be used to make future treatment decisions.
We assembled a focus group of thought leaders in pharmacogenomics to brainstorm and design the software pipeline. We hosted a one-week Hackathon at the PharmGKB at Stanford University to bring together computer programmers with scientific curators to implement version one of this tool. We will host a meeting to summarize and evaluate next steps in mid-May including the development of a manuscript and dissemination plan for the tool. This software pipeline will be made available in a Creative Commons license and disseminated in GitHub later this spring for all in the scientific community to test, explore, improve and to give us feedback. Be a part of this project! As many of our institutions are building implementation workflows for pharmacogenomics, our ability to automate some of the extraction of genes/variants of interest would be enormously helpful.
We welcome scientific input from our colleagues. If you would like to become involved in this effort, we ask that you contact firstname.lastname@example.org. Thank you!