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eMERGE Pharmacogenomics Study

A widely-held vision arising from the Human Genome Project is to use information on genomic variation to guide preventive and therapeutic decision-making for individual patients. One therapeutic area that seems especially ripe for an early test of this concept is pharmacogenomics (PGx) – the idea that variability in response to a wide range of drug therapies includes a genomic component. Variable response to therapy is an accepted feature of virtually all drug treatments and research since the 1980s and has resulted in the definition of key genes mediating drug metabolism, transport, and targets. Importantly, common variation in these genes is an increasingly well-recognized contributor, sometimes with large effects, to variability in drug responses, and as a result, recommendations for genotype-guided therapy are being disseminated by the CPIC group and others.

The goals of the eMERGE II PGx project included:

  • Develop technical and regulatory solutions to integrate pharmacogenomic information into the Electronic Health Record (EHR) in a useable fashion;
  • Assess physician and patient attitudes towards the value of pre-emptive pharmacogenomics;
  • Create strategies to educate physicians and patients in the use of genomic data; and
  • Expand our knowledge of clinically-significant genetic variants.

To accomplish these goals, we genotyped 750 patients seen at the Northwestern Medical Group (NMG) General Internal Medicine (GIM) clinic on the PGRN-Seq platform and in a CLIA-approved environment, integrated a number of these genetic variants into our EPIC-based EHR, developed decision-support for GIM physicians surrounding these variants, and tracked outcomes relating to implementation of these genetic test results, including physician actions and patient and physician attitudes and concerns.

The PGx Project built upon processes already developed for phase II of the eMERGE II parent grant. These included relationships with physician and patient advisory committees, methods to evaluate patient and physician attitudes and expectations for return of genomic results, use of clinical decision support tools for returning results, and methods for storing and parsing the genomic test result data.

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