Hu Fuli, Ma Songhua, Hu Tianliang
Key Laboratory of High Efficiency and Clean Mechanical Manufacture, School of Mechanical Engineering, Shandong University, Jinan 250061, China.
Bioengineering (Basel). 2025 Jun 12;12(6):643. doi: 10.3390/bioengineering12060643.
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.
吸入疗法在慢性呼吸道疾病中的临床疗效从根本上受到颗粒沉积模式的限制。本研究采用计算流体动力学（CFD）和响应面方法（RSM），通过多因素敏感性映射来阐明沉积决定因素之间的机制相互作用。该研究包括两个关键部分：（i）建立一个从口腔到第五代支气管的精确三维呼吸道模型；（ii）将Box-Behnken设计（BBD）实验框架与计算流体动力学模拟相结合。此外，我们还开发了一个多因素回归模型，以分析沉积决定因素之间的协同相互作用。该研究表明屏气时间与药物沉积效率之间呈正相关，揭示了关键参数的层次顺序：峰值流速>屏气时间>颗粒直径。这些发现对优化临床环境中的呼吸道药物递送策略具有重要意义。
