The molecular and cellular mechanisms of the CS-induced immune response in COPD progression are not completely understood. In particular, the issues regarding the dynamics of CS-induced immune response in COPD, the effects of cigarette smoking cessation, and the disease susceptibility remain to be elucidated [1–2]. As COPD is a chronic and progressive inflammatory disease whose dynamical time scale is usually very long (over 20 years of CS exposure ), it would be extremely difficult for real-time measurements in the clinic or the laboratory. The main objective of this paper is to use computer modeling and simulation to address these issues. As discussed above, the nodes in our network model, which bears a multiscale nature, represent the cytokines, immune cells and damaged tissues (TD) whose dynamics characterizes the progression of COPD. The interactions between these nodes are often highly nonlinear and can be described using the Hill functions. The population dynamics of the network elements are described by a set of DOEs with parameters, whose values are known or estimated from established literature. For those no experimental data are available, we performed the global sensitivity analysis to obtain order-of-magnitude estimates.