Funding: NIH KL2RR024154
Sepsis is a leading cause of acute kidney injury (AKI) in critically ill patients. Sepsis-induced AKI is associated with increased risk of death for which there is no specific treatment. Recovery from sepsis-induced AKI involves complex interactions between demographics, severity of illness, inflammation, hemodynamics, and cell signaling pathways. This project aims to model such complex networks using systems biology, mechanistic mathematical and computational modeling techniques, and biostatistics. The goal is to examine various interventions using simulation and execute a virtual “in-silico” trial of a potential intervention. This would facilitate hypothesis generation that can then be tested in prospective clinical trials.
Influential diagram illustrating interaction within a complex network that are being modeled using mechanistic approaches