Mathematical Biology Seminar Judy Day, University of Pittsburgh Tuessday Feb. 6, 2007 3:00pm in LCB 219 Modeling and Controlling Inflammation Abstract: Immunomodulation has become a focal point in the treatment of critically ill patients, as clinicians seek to manage the delicate balance between the necessity and potential hazards of inflammation in infection containment and healing. Modeling of inflammation is emerging as a desirable approach in designing effective immunomodulatory strategies, with most computational work focused on modeling molecular and systemic mechanisms of inflammation with increasing biological fidelity. Yet, there is still much to be done in the area of identifying successful strategies to combat excessive and pervasive inflammation. In the first part of the talk, a four dimensional differential equation model of the acute inflammatory response is presented in the context of repeated endotoxin administrations. Lipopolysaccharide (LPS) or endotoxin can induce an acute inflammatory response comparable to a bacterial infection. In experiments with repeated endotoxin administration the observation that a preconditioning dose can blunt the inflammatory response is known as endotoxin tolerance. Our findings support the hypothesis that endotoxin tolerance and other related phenomena can be considered as dynamic manifestations of a unified acute inflammatory response. In the second half, we use this model to investigate a prospective tool known as nonlinear model predictive control (NMPC), which may help determine suitable dose regimens in complex clinical settings. The advantage of this approach over other control algorithms is that it combines both a prediction of the future state of the system from a mathematical model and feedback from real time data measurements to successively update a sequence of control moves that will help to optimize the desired outcome for a specific scenario.