Precision Medicine and Pharmacogenomics: From One-Size-Fits-All to Data-Driven Individualized Therapy

Abstract

Precision medicine is moving away from a "one size fits all" model and moving towards the treatment of the individual patient. The paradigm shift is tied to a study of how genetic variation affects drug response, called Pharmacogenomics (PGx). This paper highlights three undeniably interrelated trends: Firstly, the need for ancestry diverse datasets for equitable implementation of PGx; secondly, a pharmacist-led economically viable model of PGx delivery; thirdly, Decoding drug-response phenotypes using a synthetic process of integrating AI with multi-omics data. Existing data suggests that the combination of AI tools for analytics, integrated multi-omics tools that incorporate metabolomics, and community implementation is all driving PGx from an area of research curiosity to a clinical standard, despite the issues of algorithmic bias, reimbursement, and translation that will require resolution. A blueprint is provided for both researchers, clinicians, and policymakers.