The sequencing of the first human genome in 2001 highlighted remarkable complexity and heterogeneity [1] and brought great anticipation in advancing our understanding of disease. The therapeutic promise implicit in research ventures like the Human Genome Project (HGP) and other advancements in genetic-genomic DNA technology lies within the concept of personalized medicine. A key element of personalized medicine is to develop medical treatment that is tailored to the specific disease process of each patient. Pharmacogenetics and pharmacogenomics (often used together or interchangeably) refer to the study of genetic differences and their effect on drug metabolism, therapeutic response, and adverse reactions (i.e., pharmacokinetics and pharmacodynamics). The genetic information can be used to guide clinical decision-making and optimize patient care. Highlighted in this review series are examples by which the use of pharmacogenetics and pharmacogenomics has promoted the advancement of molecular medicine, and started to bridge the gap between science and medicine through a shared progression across a variety of disciplines. This collection of reviews introduces the field of data science, along with the latest experimental approaches and statistical methods being used to analyze the vast amounts of large-scale, genome-based data from pharmacogenetic-pharmacogenomic studies (Penrod and Moore). Furthermore, genome-wide association studies (GWAS) are outlined as a powerful and effective tool to identify susceptibility loci and targeted pharmacotherapies for complex diseases, such as age-related macular degeneration (AMD) (Rosen, Kaushal, and SanGiovanni). Similarly, the utility of lymphoblastoid cell lines (LCLs) is reviewed as an efficient model system for performing human pharmacogenomic studies in vitro (Jack, Rotroff, and Motsinger-Reif). In terms of clinical studies, the latest pharmacogenetic-pharmacogenomic applications relating to neurological disorders, including Parkinson’s and Alzheimer’s disease, as well as common mental illnesses, such as schizophrenia (SCZ), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD) are outlined (Gilman and Mao). The growing field of anti-obesity medications, together with the genes and gene variants thought to impact their effectiveness is also presented (Guzman and Martin). Among a wide array of cardiovascularrelated topics, the timely issue of