TY - JOUR
T1 - Mechanistic simulations of inflammation
T2 - Current state and future prospects
AU - Vodovotz, Yoram
AU - Constantine, Gregory
AU - Rubin, Jonathan
AU - Csete, Marie
AU - Voit, Eberhard O.
AU - An, Gary
N1 - Funding Information:
This work was supported in part by the National Institutes of Health Grants R01-GM-67240-02 (Y.V., J.R., G.C.), P50-GM-53789-08 (Y.V., G.C.), R01-HL080926-01 (Y.V., G.C.), and R01-HL-76157-02 (Y.V., J.R., G.C.); National Institute on Disability and Rehabilitation Research Grant H133E070024 (Y.V., G.A.); National Science Foundation Grants DMS041423 and DMS0716936 (J.R.); as well as grants from the Commonwealth of Pennsylvania (Y.V.), the Pittsburgh Lifesciences Greenhouse (Y.V.), and the Pittsburgh Tissue Engineering Initiative (Y.V.).
PY - 2009/1
Y1 - 2009/1
N2 - Inflammation is a normal, robust physiological process. It can also be viewed as a complex system that senses and attempts to resolve homeostatic perturbations initiated from within the body (for example, in autoimmune disease) or from the outside (for example, in infections). Virtually all acute and chronic diseases are either driven or modulated by inflammation. The complex interplay between beneficial and harmful arms of the inflammatory response may underlie the lack of fully effective therapies for many diseases. Mathematical modeling is emerging as a frontline tool for understanding the complexity of the inflammatory response. A series of articles in this issue highlights various modeling approaches to inflammation in the larger context of health and disease, from intracellular signaling to whole-animal physiology. Here we discuss the state of this emerging field. We note several common features of inflammation models, as well as challenges and prospects for future studies.
AB - Inflammation is a normal, robust physiological process. It can also be viewed as a complex system that senses and attempts to resolve homeostatic perturbations initiated from within the body (for example, in autoimmune disease) or from the outside (for example, in infections). Virtually all acute and chronic diseases are either driven or modulated by inflammation. The complex interplay between beneficial and harmful arms of the inflammatory response may underlie the lack of fully effective therapies for many diseases. Mathematical modeling is emerging as a frontline tool for understanding the complexity of the inflammatory response. A series of articles in this issue highlights various modeling approaches to inflammation in the larger context of health and disease, from intracellular signaling to whole-animal physiology. Here we discuss the state of this emerging field. We note several common features of inflammation models, as well as challenges and prospects for future studies.
KW - Agent-based modeling
KW - Computer simulation
KW - Endotoxin
KW - Infection
KW - Inflammation
KW - Mathematical modeling
KW - Ordinary differential equations
KW - Parameter estimation
KW - Personalized medicine
KW - Preconditioning
KW - Sepsis
KW - Stochastic simulations
KW - Toll-like receptors
KW - Trauma
UR - http://www.scopus.com/inward/record.url?scp=57749172576&partnerID=8YFLogxK
U2 - 10.1016/j.mbs.2008.07.013
DO - 10.1016/j.mbs.2008.07.013
M3 - Article
C2 - 18835282
AN - SCOPUS:57749172576
SN - 0025-5564
VL - 217
SP - 1
EP - 10
JO - Mathematical Biosciences
JF - Mathematical Biosciences
IS - 1
ER -