2004 | OriginalPaper | Buchkapitel
Mathematical and Statistical Modeling of Acute Inflammation
verfasst von : Gilles Clermont, Carson C. Chow, Gregory M. Constantine, Yoram Vodovotz, John Bartels
Erschienen in: Classification, Clustering, and Data Mining Applications
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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A mathematical model involving a system of ordinary differential equations has been developed with the goal of assisting the design of therapies directed against the inflammatory consequences of infection and trauma. Though the aim is to build a model of greater complexity, which would eventually overcome some existing limitations (such as a reduced subset of inflammatory interactions, the use of mass action kinetics, and calibration to circulating but not local levels of cytokines), the model can at this time simulate certain disease scenarios qualitatively as well as predicting the time course of cytokine levels in distinct paradigms of inflammation in mice. A parameter search algorithm is developed that aids in the identification of different regimes of behaviour of the model and helps with its calibration to data. Extending this mathematical model, with validation in humans, may lead to the in silico development of novel therapeutic approaches and real-time diagnostics.