Tools and technology for multi-scale modeling of physiological systems have matured to the point where systems simulations are finding applications in drug development and predictive medicine. Indeed, disciplines of model-based drug development and systems pharmacology are beginning to impact all phases of drug development. Similarly, modeling and simulation are crucial tools for device development, and increasingly computational modeling is finding applications in simulation of the integration of physiological systems and device function. In this proposed project we will test and refine the ability of multi-scale systems physiology modeling to make specific predictions about the genotype-to-phenotype map in vertebrate organisms. Specifically, we will use an existing modeling and simulation framework (accounting for myocardial energy metabolism, cardiac mechanics, and whole-body cardiovascular systems dynamics) to predict the effects of knockouts of specific genes involved in purine metabolism on whole-body phenotype. These predictions will be tested using targeted gene knockdown using CRISPR/Cas9 technology in rat models. By testing and refining our ability to predict whole-body impacts of molecular genetic perturbations we will develop a uniquely powerful understanding of genotype-to-phenotype relationships in higher organisms. Validation of specific targets in purine metabolism will potentially point to an entirely new set of therapeutic targets in heart disease. More broadly, demonstration of the ability to make successful genotype-to-phenotype predictions has the potential to find broad applications in the field of quantitative systems pharmacology, potentially leading to far reaching applications.
Two decades after the report of the first draft sequence of the human genome we largely lack a systematic understanding of how variability at the molecular genetic level influences whole-organism phenotype. In other words, for the most part we do not have a working understanding of the genotype-to-phenotype map in higher organisms. Here we propose to use gene editing along with sophisticated phenotype evaluation techniques and computational simulation to test our ability to predict the effects of specific molecular genetic changes on whole-organism function in rats.
