Generating evidence for precision medicine: considerations made by the Ubiquitous Pharmacogenomics Consortium when designing and operationalizing the PREPARE study

Objectives

Pharmacogenetic panel-based testing represents a new model for precision medicine. A sufficiently powered prospective study assessing the (cost-)effectiveness of a panel-based pharmacogenomics approach to guide pharmacotherapy is lacking. Therefore, the Ubiquitous Pharmacogenomics Consortium initiated the PREemptive Pharmacogenomic testing for prevention of Adverse drug Reactions (PREPARE) study. Here, we provide an overview of considerations made to mitigate multiple methodological challenges that emerged during the design.

Methods

An evaluation of considerations made when designing the PREPARE study across six domains: study aims and design, primary endpoint definition and collection of adverse drug events, inclusion and exclusion criteria, target population, pharmacogenomics intervention strategy, and statistical analyses.

Results

Challenges and respective solutions included: (1) defining and operationalizing a composite primary endpoint enabling measurement of the anticipated effect, by including only severe, causal, and drug genotype-associated adverse drug reactions; (2) avoiding overrepresentation of frequently prescribed drugs within the patient sample while maintaining external validity, by capping drugs of enrolment; (3) designing the pharmacogenomics intervention strategy to be applicable across ethnicities and healthcare settings; and (4) designing a statistical analysis plan to avoid dilution of effect by initially excluding patients without a gene–drug interaction in a gatekeeping analysis.

Conclusion

Our design considerations will enable quantification of the collective clinical utility of a panel of pharmacogenomics-markers within one trial as a proof-of-concept for pharmacogenomics-guided pharmacotherapy across multiple actionable gene–drug interactions. These considerations may prove useful to other investigators aiming to generate evidence for precision medicine.