A Whole-Body Physiological Model of Sepsis and Associated Treatments, Designed in the BioGears Engine
Sepsis is a debilitating condition associated with a high mortality rate that greatly strains hospital resources. Though advances have been made in improving sepsis diagnosis and treatment, our understanding of the disease is far from complete. We will present a mathematical model of sepsis that has the potential to explore underlying biological mechanisms and patient phenotypes that contribute to variability in septic patient outcomes. We will start by giving an overview of BioGears, a robust open source model of a virtual patient, then describe the sepsis pathophysiology model and how it connects to the various other systems in the body. We will briefly touch on various submodels that play a role in the patient response, such as the nervous system and tissue diffusion. We will then provide an overview of how we validate this model in the context of scenarios that compare sepsis treatment regimens. As such, we demonstrate the utility of this model as a tool to augment sepsis research and as a training platform to educate medical staff.
Password: “arizona” (all lower case)