Pharmacogenomics and Precision Psychiatry

Globally psychiatric disorders present a major health concern. Currently, innovations in treatment are limited by (i) lack of biomarkers for symptom change and diagnosis, (ii) suboptimal pharmacotherapeutic options that are limited to a trial-and-error approach, and (iii) insufficient leveraging of predictive technologies. This chapter documents developments in the field of pharmacogenetics, which is based on examining the genetic variants of a given individual in order to predict the medications that they will have the best probability of responding to, with a minimum of side effects. Newer approaches that integrate predictive computational technologies (i.e., artificial intelligence and machine learning) are also described. When pharmacogenetic (PGx) testing information is used to guide drug selection, treatment adherence increases, adverse reactions are reduced, and significantly increased rates of remission are achieved. However, the uptake of PGx testing faces several challenges. The chapter discusses how challenges are being met with increasingly larger datasets, including randomized controlled trials, clinical utility analyses, and cost-effectiveness.