The clinical efficacy of inhalation therapy in chronic respiratory diseases is fundamentally constrained by particle deposition patterns. This study employs computational fluid dynamics (CFD) and response surface methodology (RSM) to elucidate the mechanistic interplay of deposition determinants through multifactorial sensitivity mapping. The study comprises two key components: (i) the development of an accurate three-dimensional respiratory airway model spanning from the oral cavity to the fifth-generation bronchi and (ii) the integration of a Box-Behnken Design (BBD) experimental framework with computational fluid dynamics simulations. Furthermore, we developed a multifactorial regression model to analyze the synergistic interactions among deposition determinants. The study demonstrated a positive correlation between breath-holding time and drug deposition efficiency, revealing a hierarchical order of critical parameters: peak flow rate > breath-holding time > particle diameter. These findings have important implications for optimizing respiratory drug delivery strategies in clinical settings.
Keywords: aerosol dynamics; breath-holding; computational fluid dynamics; drug delivery; inhaled medication; multiphase flow; respiratory modeling.