Judy Day
Using nonlinear model predictive control to find optimal
therapeutic strategies to modulate inflammation
Abstract
Modulation of the inflammatory response has become a key focal point in
the treatment of critically ill patients. Much of the computational work
in this emerging field has been carried out with the goal of unraveling
the primary drivers, interconnections, and dynamics of systemic
inflammation. To translate these theoretical efforts into clinical
approaches, the proper biological targets and specific manipulations must
be identified. In this work, we pursue this goal by implementing a
nonlinear model predictive control (NMPC) algorithm in the context of a
reduced computational model of the acute inflammatory response to severe
pathogenic infection. Our results imply that a combination of
computational modeling and NMPC may be of practical use in suggesting
novel immuno-modulatory strategies for the treatment of intensive care
patients.
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