COMPUTATIONAL MODELS OF INFLAMMATION AND WOUND HEALING

The acute inflammatory response to biological stress involves a highly conserved cascade of events mediated by a large array of cells and molecules. While not intrinsically detrimental, inflammation can cause secondary or ancillary damage to tissues, which in turn leads to the production of molecules that amplify inflammatory response and, in extreme cases, promote organ dysfunction and death. Therefore, there is a need to identify and modulate dysregulated inflammatory processes while allowing healthy inflammation to carry on. While in vitro and in vivo studies have brought many insights into the components and dynamics of the inflammatory response, computational techniques are becoming increasingly relevant to tease out complex relationships and inter-dependencies that may not be directly measureable. In this dissertation, we explore a computational model of pressure ulcer formation that generates tissue-realistic output and clinically-relevant predictions. By simulating basic inflammatory mechanisms and ischemia/reperfusion injury to soft tissue, our model spontaneously produces both resolving and ulcerative inflammatory patterns from a single set of parameter values. We use statistical methods to explore which mechanisms in the model are responsible for this spontaneous bifurcation. We also use data-driven methods to examine dynamics of inflammatory mediators during in vitro murine hepatocellular stress. Our results lead to identification of MCP-1 as a clinically-predictive inflammatory mediator in human trauma patients