Experimental and Numerical Investigation of Multiphase (Solid-Liquid-Gas) Flow: Application to Respiratory Drug Delivery

呼吸系统疾病的有效治疗依赖于吸入器产生的气雾剂/颗粒/液滴的性质和药物在肺部的沉积效率，这需要了解药物颗粒的空气动力学行为。尽管吸入器技术取得了进步，但药物沉积效率仍为10%-50%。我对多相(固-液-气)流的研究主要集中在药物吸入系统中固体颗粒、液滴和气泡之间的相互作用。短期目标是：(1)了解加压米剂量、干粉和软雾吸入器在药物气雾剂输送过程中的多相流机制；(2)开发计算流体动力学(CFD)模型来模拟吸入器-口-喉路径。长期目标是将药物沉积与吸入器的设计和操作联系起来，并最终与药物沉积效率联系起来。短期目标1将在我在路易斯安那大学的多相流实验室使用下一代ImpactorTM(NGITM)系统来实现。NGI包括各种吸入器装置、口咽部感应口和串级冲击器。吸入器装置连接到感应口，感应口启动给定剂量。在每次测试之后，在NGI的每个阶段中沉积的药物的质量被量化。智能在线颗粒分析技术(“SOPAT”)探头将被用来研究设计参数对吸入器设备性能的影响。它测量药物气雾剂在口腔-咽喉呼吸道内的输送和流动模式，使我们能够识别和消除导致气雾剂、颗粒和液滴流动病理的条件。对于短期目标2，CFD和离散元模拟将模拟药物气雾剂、颗粒和液滴在口腔-咽喉呼吸道中的流动和相互作用。NGI和SOPAT探测器数据将用于改进和验证模型。采用响应面方法的统计实验设计，预测给定参数(如流速)下的肺沉积效率，以确定使药物沉积效率最大化的最佳参数值。该计划将使用实验、数值和理论方法来解决与吸入器设备设计相关的基本挑战。它将评估吸入器的性能，为升级现有设计提供指导，并促进新设备的设计。这将通过更有效地使用药物来降低成本，加强药物输送监测和控制，并增加现有吸入系统的吞吐量。改进的吸入器设备将为加拿大制药业做出贡献。研究成果将通过治疗肺部疾病和减轻空气污染的影响来提高人类健康和生活质量，预计空气污染将随着全球气候变化而增加。该计划将对HQP进行多相流、药物输送系统和先进计算技术方面的培训，这将支持加拿大未来的经济发展。

Effective treatment of respiratory diseases depends on the properties of the aerosol/particles/droplets produced by the inhaler and the drug deposition efficiency in the lungs, which requires understanding drug particle aerodynamic behavior. Despite advances in inhaler device technology, drug deposition efficiency is 10-50%. My research in multiphase (solid-liquid-gas) flow focuses on interactions between solid particles, liquid droplets, and gas bubbles in drug inhalation systems. The short-term objectives are to: (1) understand the mechanisms of multiphase flow during drug aerosol delivery by pressurized meter-dose, dry powder, and soft mist inhalers; and (2) develop computational fluid dynamics (CFD) models to simulate inhaler-mouth-throat pathways. The long-term objective is to link drug deposition to inhaler design and operation and ultimately to drug deposition efficiency. Short-term objective 1 will be achieved using the Next Generation ImpactorTM (NGITM) system in my multiphase flow laboratory at LU. The NGI comprises various inhaler devices, a mouth-throat induction port, and a cascade impactor. An inhaler device is connected to the induction port, which actuates a given dose. After each test, the mass of the drug deposited in each stage of the NGI is quantified. A smart online particle analysis technology ("SOPAT") probe will be used to investigate the effect of design parameters on inhaler device performance. It measures the drug aerosol delivery and flow pattern inside the mouth-throat airway and allows us to identify and eliminate conditions leading to aerosol, particle, and droplet flow pathologies. For short-term objective 2, CFD and discrete element modeling will simulate drug aerosol, particle, and droplet flow and interactions in the mouth-throat airway. NGI and SOPAT probe data will be used to refine and validate the models. The statistical experimental design with response surface methodology will be applied to predict the lung deposition efficiency for a given parameter (e.g., flow rate) to determine the optimum parameter value to maximize drug deposition efficiency. The program will use experimental, numerical, and theoretical methods to address fundamental challenges related to inhaler device design. It will assess the performance of inhalers, provide guidance to upgrade current designs, and facilitate design of new devices. This will lower costs through more efficient use of drugs, enhance drug delivery monitoring and control, and increase throughput for existing inhalation systems. Improved inhaler devices will contribute to the Canadian pharmaceutical industry. Research outcomes will enhance human health and quality of life by treating pulmonary disease and mitigating the effects of air pollution, which is expected to increase with global climate change. The program will train HQP in multiphase flow, drug delivery systems, and advanced computational techniques, which will support future economic development in Canada.