Gary An1. 1. Department of Trauma, Cook County Hospital, Chicago, IL, USA.
Abstract
OBJECTIVES: To introduce a form of mathematical modeling, agent-based modeling (ABM), and demonstrate its potential uses in the evaluation of the dynamics of the innate immune response (IIR) and the development of possible treatments for systemic inflammatory response syndrome (SIRS)/multiple organ failure (MOF). RATIONALE: The IIR can be categorized as a complex system that responds to interventions in a nonintuitive fashion, leading to difficulty in translating basic science knowledge into effective treatments for SIRS/MOF. It is proposed that ABM is particularly well suited to examining the complex interactions of the IIR and its disordered states of SIRS/MOF. STUDY DESIGN: Computer simulation and mathematical modeling. DATA SOURCE: Review articles on components and mechanisms involved in the IIR. Published results from phase III anticytokine/mediator trials. Published results from smaller clinical trials and animal studies. MAIN RESULTS: An abstract ABM of the IIR was created. The model reproduces the general behavior of the IIR with respect to outcome and cause of system "death." Patterns of levels of individual cytokines matched patterns of measured cytokines reported in the existing literature. Clinical trials of anticytokine therapy were simulated and produced outcomes qualitatively similar to those reported in the literature. A series of hypothetical treatment regimes (variation of dose and length of treatment [anti-tumor necrosis factor and anti-interleukin-1], anti-CD-18, and multiple-drug regimes [combination of anti-tumor necrosis factor, anti-interleukin-1, and anti-CD-18]) were formulated and implemented in the ABM. None of the simulated therapies showed a statistically significant improvement in system mortality. CONCLUSIONS: Presented herein is an abstracted ABM of the IIR. This model is intended primarily as an introduction to and demonstration of this technique. However, even this relatively simple model demonstrates counterintuitive system responses and the difficulty of effectively manipulating a complex system like the IIR. ABM may provide a synthetic, analytical platform to integrate basic science data on the IIR, thus eventually aiding in formulating and testing future mediator-directed therapies for SIRS/MOF before clinical trials, and it may provide insights into directions of future research.
OBJECTIVES: To introduce a form of mathematical modeling, agent-based modeling (ABM), and demonstrate its potential uses in the evaluation of the dynamics of the innate immune response (IIR) and the development of possible treatments for systemic inflammatory response syndrome (SIRS)/multiple organ failure (MOF). RATIONALE: The IIR can be categorized as a complex system that responds to interventions in a nonintuitive fashion, leading to difficulty in translating basic science knowledge into effective treatments for SIRS/MOF. It is proposed that ABM is particularly well suited to examining the complex interactions of the IIR and its disordered states of SIRS/MOF. STUDY DESIGN: Computer simulation and mathematical modeling. DATA SOURCE: Review articles on components and mechanisms involved in the IIR. Published results from phase III anticytokine/mediator trials. Published results from smaller clinical trials and animal studies. MAIN RESULTS: An abstract ABM of the IIR was created. The model reproduces the general behavior of the IIR with respect to outcome and cause of system "death." Patterns of levels of individual cytokines matched patterns of measured cytokines reported in the existing literature. Clinical trials of anticytokine therapy were simulated and produced outcomes qualitatively similar to those reported in the literature. A series of hypothetical treatment regimes (variation of dose and length of treatment [anti-tumor necrosis factor and anti-interleukin-1], anti-CD-18, and multiple-drug regimes [combination of anti-tumor necrosis factor, anti-interleukin-1, and anti-CD-18]) were formulated and implemented in the ABM. None of the simulated therapies showed a statistically significant improvement in system mortality. CONCLUSIONS: Presented herein is an abstracted ABM of the IIR. This model is intended primarily as an introduction to and demonstration of this technique. However, even this relatively simple model demonstrates counterintuitive system responses and the difficulty of effectively manipulating a complex system like the IIR. ABM may provide a synthetic, analytical platform to integrate basic science data on the IIR, thus eventually aiding in formulating and testing future mediator-directed therapies for SIRS/MOF before clinical trials, and it may provide insights into directions of future research.
Authors: Panteleimon D Mavroudis; Jeremy D Scheff; Steve E Calvano; Stephen F Lowry; Ioannis P Androulakis Journal: Physiol Genomics Date: 2012-04-17 Impact factor: 3.107
Authors: Yoram Vodovotz; Gregory Constantine; James Faeder; Qi Mi; Jonathan Rubin; John Bartels; Joydeep Sarkar; Robert H Squires; David O Okonkwo; Jörg Gerlach; Ruben Zamora; Shirley Luckhart; Bard Ermentrout; Gary An Journal: Immunopharmacol Immunotoxicol Date: 2010-06 Impact factor: 2.730
Authors: C Anthony Hunt; Glen E P Ropella; Li Yan; Daniel Y Hung; Michael S Roberts Journal: J Pharmacokinet Pharmacodyn Date: 2006-10-19 Impact factor: 2.745
Authors: Yoram Vodovotz; Gilles Clermont; C Anthony Hunt; Rolf Lefering; John Bartels; Ruediger Seydel; John Hotchkiss; Shlomo Ta'asan; Edmund Neugebauer; Gary An Journal: J Crit Care Date: 2007-03 Impact factor: 3.425
Authors: C Anthony Hunt; Glen E P Ropella; Tai Ning Lam; Jonathan Tang; Sean H J Kim; Jesse A Engelberg; Shahab Sheikh-Bahaei Journal: Pharm Res Date: 2009-09-09 Impact factor: 4.200