Pharmacogenomics Workflow: Identifying Biomarkers and Treatment Options

Abstract Pharmacogenomics, the study of how an individual's genetic makeup affects their response to drugs, has undergone rapid advancements. This has occurred alongside a decrease in the cost of genotyping technology, making implementation of pharmacogenomics into clinical practice increasingly feasible. Personalized medicine leveraging pharmacogenomics is gaining momentum to optimize drug choice, dosage, efficacy, and safety for individual patients, moving away from the "one drug fits all" or "one dose fits all" strategies. This shift towards a more personalized approach presents an opportunity for healthcare providers to enhance clinical outcomes, reduce adverse drug reactions, and achieve cost-effective healthcare by integrating pharmacogenomics into routine clinical practice. As the cost of exome and whole-genome sequencing declines, pharmacogenomic data analysis becomes increasingly relevant in next-generation sequencing (NGS) based tests. These tests are widely adopted to diagnose rare diseases, to analyze mutation profiles of tumors, to provide reproductive genetic services, and perform genetic screening in newborns. NGS testing laboratories employ analysis software featuring integrated clinical decision support tools to process the extensive range of identified sequence variants proficiently. Although the FDA often requires that gene-drug associations be included in drug labeling, and numerous clinically relevant data sources exist (e.g., PharmVar and PharmGKB), there is currently a lack of integration of these resources into NGS testing workflows. This means that drug-gene interactions that can lead to severe adverse effects in patients are often overlooked. In this project, we will begin developing pharmacogenetics analytics capability as an integrated component of NGS-based genetic testing. This would involve developing and validating methods for automating identification and interpretation of pharmacogenetic variants, and integrating these findings into clinical reports for healthcare providers. Moreover, the project necessitates the evaluation of the clinical utility of pharmacogenetic testing in next-generation sequencing, assessing its influence on treatment decisions, patient outcomes, and healthcare costs. Overall, the project aims to establish pharmacogenetic testing as a routine component of next-generation sequencing, providing clinicians with valuable information to optimize medication selection and dosing for their patients.