University of Cambridge, Department of Engineering, Trumpington Street, CB2 1PZ, UK.
University of Hertfordshire, Department of Pharmacy, Pharmacology and Postgraduate Medicine, College Lane, AL10 9AB, UK.
Int J Pharm. 2018 Dec 20;553(1-2):37-46. doi: 10.1016/j.ijpharm.2018.10.021. Epub 2018 Oct 10.
In a passive dry powder inhaler (DPI) a patient inhales to entrain drug powder. The goal of this study is to demonstrate experimentally that an Eulerian-Eulerian (EE CFD) computational fluid dynamics (CFD) method can accurately predict the entrainment of the dry powder formulation in DPIs. A CFD method that makes accurate predictions of the entrainment process can be applied in DPI design and optimization processes. Three different DPI entrainment geometries were tested. For each geometry, a transparent entrainment module was prepared. In each experiment, the chosen entrainment module was first filled with lactose powder and attached to an inhalation simulator (a computer controlled pump). The entrainment process was recorded with a high-speed camera. The resulting video footage was analysed and compared with CFD predictions. The observed distribution of powder in the entrainment compartment and the measured rate of drug entrainment were in good agreement with CFD predictions. Through a process of experimental validation, this study established the first demonstration that two-dimensional EE CFD methodology provides robust and accurate predictions of aerosol generation from DPI entrainment chambers. The findings support the wider application of EE CFD for the design optimization of DPI devices.
在被动干粉吸入器（DPI）中，患者通过吸入来夹带药物粉末。本研究的目的是通过实验证明，欧拉-欧拉（EE）计算流体动力学（CFD）方法可以准确预测 DPI 中干粉制剂的夹带。能够准确预测夹带过程的 CFD 方法可应用于 DPI 设计和优化过程。测试了三种不同的 DPI 夹带几何形状。对于每个几何形状，都准备了一个透明的夹带模块。在每个实验中，首先将选定的夹带模块填充乳糖粉末并连接到吸入模拟器（计算机控制的泵）上。夹带过程用高速摄像机记录。对所得视频片段进行分析，并与 CFD 预测进行比较。夹带室中粉末的观察分布和测量的药物夹带速率与 CFD 预测非常吻合。通过实验验证过程，本研究首次证明，二维 EE CFD 方法为 DPI 夹带室中的气溶胶生成提供了强大而准确的预测。研究结果支持更广泛地应用 EE CFD 来优化 DPI 装置的设计。
