Our mission is to develop new ways to identify and treat people with insulin resistance—an important cause of type 2 diabetes, fatty liver, heart attacks, strokes, and cancer. We live in a world of “big data”—low-cost genomics, and real-time health monitoring, which promises new medicines and a more precise approach to individual treatment. While we have accumulated large genome-scale and now phenome-scale data, we are challenged by a lack of understanding at the level of individual genes and patients. For example, hundreds of thousands of protein-altering human genetic variants have been identified in sequenced populations in almost every gene but we remain unable to interpret these “experiments-of-nature” to provide actionable clinical information to individuals or mechanistic insights on gene function for therapeutic development. We propose to unlock these experiments-of-nature using massively parallel bioassays to functionally characterize variants prospectively, thus enabling a genotype:function:phenotype approach. This approach will guide research programs to discover new genes that can become drug targets and novel diagnostics that can individualize treatments.