The drug discovery process classically revolves around a set of biochemical and cellular assays to drive potency optimization and structural-activity relationship models. Layered on top of these concepts is the inclusion of molecular features that affect final drug use, things like: bioavailability, toxicity, stability, solubility, formulation, route of administration, etc. Paradoxically, most drugs entering clinical trials are only tested in a handful of human genetic backgrounds before they are given to people. Here we review efforts and opine on the use of large scale in vitro cellular and in vivo models that attempt to model human disease and include diversity found in the human genetic population. Because hundreds to thousands of individual assays are needed to scratch the surface of human genetic diversity, sophisticated high throughput automation technologies or pooling and deconvolution strategies are required. Characterization of each model needs to be extensive to enable non-biased informatics based modeling. Such approaches will enable deep understanding of genetic to pharmacological response and result in new methods for patient stratification in the clinic. Oncology medicines and cancer genetics have been paving the way for these approaches and we expect to see continued expansion to other fields such as immunology and neuroscience.