Preemptive genotyping for personalized medicine: design of the right drug, right dose, right time-using genomic data to individualize treatment protocol

Mayo Clin Proc. 2014 Jan;89(1):25-33. doi: 10.1016/j.mayocp.2013.10.021.


Objective: To report the design and implementation of the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment protocol that was developed to test the concept that prescribers can deliver genome-guided therapy at the point of care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated into the electronic medical record (EMR).

Patients and methods: We used a multivariate prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among the Mayo Clinic Biobank participants, with a recruitment goal of 1000 patients. We used a Cox proportional hazards model with variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR.

Results: The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for International Classification of Diseases, Ninth Revision codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 1013 (51%) provided blood samples, 256 (13%) declined participation, 555 (28%) did not respond, and 176 (9%) consented but did not provide a blood sample within the recruitment window (October 4, 2012, through March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS was integrated into the EMR and flagged potential patient-specific drug-gene interactions and provided therapeutic guidance.

Conclusion: This translational project provides an opportunity to begin to evaluate the impact of preemptive sequencing and EMR-driven genome-guided therapy. These interventions will improve understanding and implementation of genomic data in clinical practice.

Keywords: CAB; CAP; CDS; CGSL; CLIA; Clinical Genome Sequencing Laboratory; Clinical Laboratory Improvement Amendments; College of American Pathologists; Community Advisory Board; EMR; Electronic Medical Record and Genomics; FDA; Food and Drug Administration; NGS; PGL; PGRN; PGx; Personalized Genomics Laboratory; Pharmacogenomics Research Network; RIGHT; The Right Drug, Right Dose, Right Time—Using Genomic Data to Individualize Treatment; clinical decision support; eMERGE; electronic medical record; next-generation sequencing; pharmacogenomics.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Atherosclerosis / drug therapy
  • Cohort Studies
  • Decision Making
  • Diabetes Mellitus / drug therapy
  • Dyslipidemias / drug therapy
  • Electronic Health Records
  • Female
  • Genetic Testing / standards*
  • Genotyping Techniques
  • Hematopoiesis / drug effects
  • Humans
  • Hydroxymethylglutaryl-CoA Reductase Inhibitors / therapeutic use
  • Hypertension / drug therapy
  • Male
  • Middle Aged
  • Pharmacogenetics / methods*
  • Pharmacogenetics / standards
  • Pilot Projects
  • Practice Guidelines as Topic*
  • Precision Medicine / methods*
  • Precision Medicine / standards
  • Predictive Value of Tests
  • United States


  • Hydroxymethylglutaryl-CoA Reductase Inhibitors