Fast and frugal trees: translating population-based pharmacogenomics to medication prioritization

Abstract

Aim: Fast and frugal decision trees (FFTs) can simplify clinical decision making by providing a heuristic approach to contextual guidance. We wanted to use FFTs for pharmacogenomic knowledge translation at point-of-care. Materials & Methods: The Pharmacogenomics for Every Nation Initiative (PGENI), an international nonprofit organization, collects data on regional polymorphisms as a predictor of metabolism for individual drugs and dosages. We advanced FFTs to work with PGENI pharmacogenomic data to produce medication recommendations that are accurate, transparent and straightforward to automate. Results: By streamlining medication selection processes in the PGENI workflow, information technology applications can now be deployed. Conclusion: We developed a decision tree approach that can translate pharmacogenomic data to provide up-to-date recommended care for populations based on their medication-specific markers.