Pharmacogenomics can be described as the scientific process of selecting a therapeutic regimen for a patient with a given condition that takes account of patient specific responses and drug side effects using gene panels and single nucleotide polymorphism (SNP) data as a guide. Evidence-based clinical practice guidelines are essential for the viability of pharmacogenomics. Appropriately applied, pharmacogenomics facilitated by guideline-based automated clinical decision support (CDS) tools can maximize the efficiency of the prescription process.
In 2015, the Colorado Center for Personalized Medicine (CCPM), in partnership with University of Colorado Health (UCHealth), established the CCPM Biobank Research Study to facilitate large-scale genomics and other ‘omics’-based research to advance personalized medicine for UCHealth patients.
“As of January 2020, over 120,000 participants have enrolled in the CCPM Biobank Research Study and approximately 53,000 of those individuals have had a blood sample collected for genomic analysis. Key operational units within CCPM include: the Clinical Laboratory Improvement Amendments (CLIA)-certified Biobank Laboratory; the enterprise data warehouse, Health Data Compass; and the computing infrastructure, the Translational Informatics and Computational Resource (TICR).”
CLIA-certification allows the biobank to return clinical genetic test results back to research study participants and their electronic health record (EHR). Pharmacogenomic information, genetic diagnoses, carrier status, and predictors of disease risk (e.g., secondary or incidental findings) are examples of data that may be returned. Pharmacogenomic data comprised the first phase of pre-emptive return of biobank patient results to the EHR. This process is overseen by The CCPM Pharmacogenomics Implementation Committee Colorado (PICColo).
The pre-emptive clinical pharmacogenomic implementation initiative of the health system-wide research biobank at the University of Colorado was recently described in detail in an institutional profile published in the journal Pharmacogenomics. The initiative sought to address:
- How do we facilitate the use of pharmacogenomic results in direct patient care, when these results are generated as part of a biobank research study?
- How can the results of pre-emptive genotyping be returned to the EHR to support future timely clinical decision-making based on evolving pharmacogenomic knowledge?
- What pharmacogenomic results and medications should be targeted first in a heterogeneous biobank population?
- What is the best way to educate clinicians and patients about this unique pharmacogenomic implementation approach?
- What resources are required to design and deploy scalable EHR-based pharmacogenomic CDS tools across a large healthcare system for this initiative?
- What are the challenges and lessons learned from delivering clinical pharmacogenomic results to clinicians and patients via this hybrid model?