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使用计算流体动力学优化鼻喷雾剂参数以实现高效药物递送。

Optimising nasal spray parameters for efficient drug delivery using computational fluid dynamics.

作者信息

Inthavong K, Tian Z F, Tu J Y, Yang W, Xue C

机构信息

School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, PO Box 71, Bundoora Vic 3083, Australia.

出版信息

Comput Biol Med. 2008 Jun;38(6):713-26. doi: 10.1016/j.compbiomed.2008.03.008. Epub 2008 May 12.

Abstract

Experimental images from particle/droplet image analyser (PDIA) and particle image velocimetry (PIV) imaging techniques of particle formation from a nasal spray device were taken to determine critical parameters for the study and design of effective nasal drug delivery devices. The critical parameters found were particle size, diameter of spray cone at a break-up length and a spray cone angle. A range of values for each of the parameters were ascertained through imaging analysis which were then transposed into initial particle boundary conditions for particle flow simulation within the nasal cavity by using Computational Fluid Dynamics software. An Eulerian-Lagrangian scheme was utilised to track mono-dispersed particles (10 and 20 microm) at a breathing rate of 10 L/min. The results from this qualitative study aim to assist the pharmaceutical industry to improve and help guide the design of nasal spray devices.

摘要

采用来自粒子/液滴图像分析仪(PDIA)的实验图像以及粒子图像测速(PIV)成像技术,对鼻腔喷雾装置形成颗粒的过程进行成像,以确定有效鼻腔给药装置研究和设计的关键参数。所发现的关键参数包括粒径、在破碎长度处的喷雾锥直径以及喷雾锥角。通过成像分析确定了每个参数的一系列值,然后利用计算流体动力学软件将这些值转换为鼻腔内颗粒流模拟的初始颗粒边界条件。采用欧拉-拉格朗日方案,以10升/分钟的呼吸速率跟踪单分散颗粒(10和20微米)。这项定性研究的结果旨在协助制药行业改进并指导鼻腔喷雾装置的设计。

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