Presentation description

This project aims to evaluate the clinical utility of reporting actionable pharmacogenetic (PGx) information using next-generation sequencing (NGS) data generated from exomes, genomes, and targeted panels. As clinical testing for inherited disorders increasingly transitions to NGS-based methods, especially for whole genome applications, the potential to expand pharmacogenomic testing is significant. However, the implementation of PGx testing using NGS data poses key challenges, such as defining what is reportable and reducing the risk of over-interpreting data that may not be clinically actionable.

Working under the guidance of Dr. Yuan Ji at ARUP Laboratories, this project will assess the feasibility of identifying clinically actionable variants in selected PGx genes using existing ARUP clinical data. Specifically, the project will (1) establish the reportable range for selected PGx genes based on current ARUP guidelines and data from NGS panels, whole exomes, and whole genomes; (2) define a clinical workflow for PGx variant reporting; (3) analyze retrospective NGS datasets to extract insights on the clinical value and limitations of PGx profiling; and (4) develop a framework for classifying newly identified PGx variants in clinical settings.

The project strategy involves retrospective analysis of de-identified clinical NGS data with no need for wet-lab experimentation or patient recontact. Genes of interest include high impact pharmacogenes such as DPYD and NUDT15, which are relevant to drug metabolism and response. The ultimate goal is to improve the clinical accuracy and reliability of NGS-based PGx testing, support decision-making in patient care, and guide future policy around the integration of PGx results into routine genomic testing workflows