Combined Experimental/Computational Species Translation Modeling Tests

In order to optimize and enhance human performance, we must understand human biology in terms of computational systems models. However, limitations in undertaking in vivo experimental perturbations and measurements in humans generally render construction of such models largely dependent on data generated in animal studies. Over the past few years, the Lauffenburger laboratory has developed a systems biology framework for building computational models that translate molecular / cellular pathways and processes discerned in animal models to predict operation in human contexts, showing promising success in terms of literature-based validation. The current challenge now is that it is difficult to directly test translation model predictions in human in vivo experiments because such tests would require a great degree of confidence in our novel computational modeling approach on the part of traditional bioscientists. To overcome this challenge, we will demonstrate the intrinsic capability of our approach for translation between animal and human biology using in vitro cell culture experiments. Since the mathematical framework is agnostic to whether the translation deals with in vitro or in vivo contexts, if we can validate our approach on in vitro applications as a foundational step there should be increased confidence toward in vivo applications.