Pharmacogenomics in the Era of “Big Data” and Advanced Computational Approaches

Abstract

Undoubtedly, next generation sequencing (NGS) technologies have led to the production of a voluminous amount of data, which can be exploited towards the delineation and identification of novel pharmacogenomics (PGx) associations. Herein, we describe how NGS and genome-wide association (GWA) technologies have changed the landscape of the pharmacogenomics field, whilst proceeding with thorough details on the contribution of rare pharmacogenomics variants to the heritability of drug response trait. Moreover, we summarize some state-of-the-art text mining techniques which if harnessed properly can lead to a plethora of PGx retrieved associations. Overall, we conclude by stating that there is often a knowledge gap between (clinical) pharmacologists and researchers who exploit (pharmaco)genomics big data by using advanced computing methods. To overcome the limited number of advanced computational, statistical and mathematical methods and protocols, we propose a broad implementation and standardization of NGS techniques that should be explored by the PGx community.