Department of Biomedical Engineering, University of Massachusetts, 1 University Ave., Lowell, MA 01854, USA.
Department of Aerospace, Industrial, and Mechanical Engineering, California Baptist University, 8432 Magnolia Ave, Riverside, CA 92504, USA.
Int J Pharm. 2022 Jul 25;623:121920. doi: 10.1016/j.ijpharm.2022.121920. Epub 2022 Jun 15.
Most previous numerical studies of inhalation drug delivery used monodisperse aerosols or quantified deposition as the ratio of deposited particle number over the total number of released particles (i.e., count-based). These practices are reasonable when the aerosols have a sufficiently narrow size range. However, spray droplets from metered-dose inhalers (MDIs) are often polydisperse with a wide size range, so using monodisperse aerosols and/or count-based deposition quantification may lead to significant errors. The objective of this study was to develop a mass-based dosimetry method and evaluate its performance in lung delivery in a mouth-lung (G9) geometry with an albuterol-CFC inhaler. The conventional practices (monodisperse and polydisperse-count-based) were also simulated for comparison purposes. The MDI actuation in the open space was studied using both high-speed imaging and LES-Lagrangian simulations. Experimentally measured spray velocities and size distribution were implemented in the computational model as boundary conditions. Good agreement was achieved between recorded and simulated spray plume evolution spatially and temporally. The polydisperse-mass-based predictions of MDI doses compared favorably with the measurements in all three regions considered (device, mouth-throat, and lung). Significant errors in MDI regional deposition were predicted using the monodisperse and count-based methods. The new polydisperse-mass-based method also predicted local deposition hot spots that were one order of magnitude higher in intensity than the two conventional methods. The results of this study highlighted that a presentative polydisperse size distribution and appropriate deposition quantification method should be applied to reliably predict the MDI drug delivery in the human respiratory tract.
大多数先前的吸入药物输送数值研究使用单分散气溶胶或通过沉积粒子数与释放粒子总数的比值来量化沉积（即基于计数）。当气溶胶具有足够窄的粒径范围时，这些做法是合理的。然而，计量吸入器（MDI）的喷雾液滴通常具有较宽的粒径范围，因此使用单分散气溶胶和/或基于计数的沉积量化可能会导致显著的误差。本研究的目的是开发一种基于质量的剂量测定方法，并在具有沙丁胺醇-CFC 吸入器的口腔-肺（G9）几何形状中评估其在肺输送中的性能。还模拟了常规实践（单分散和多分散-基于计数）进行比较。使用高速成像和 LES-Lagrangian 模拟研究了开放空间中的 MDI 致动。实验测量的喷雾速度和粒径分布作为边界条件在计算模型中实施。记录的和模拟的喷雾羽流的空间和时间演化之间达成了良好的一致。多分散质量基的 MDI 剂量预测与所考虑的所有三个区域（装置、口腔-咽喉和肺）的测量值相比表现良好。使用单分散和基于计数的方法预测 MDI 区域沉积会产生显著误差。新的多分散质量基方法还预测了局部沉积热点，其强度比两种常规方法高一个数量级。这项研究的结果强调，应该应用有代表性的多分散粒径分布和适当的沉积量化方法来可靠地预测人类呼吸道中的 MDI 药物输送。
