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用体内数据验证药物气雾剂沉积的计算流体动力学预测

Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data.

作者信息

Tian Geng, Hindle Michael, Lee Sau, Longest P Worth

机构信息

Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, 401 West Main Street, P.O. Box 843015, Richmond, Virginia, 23284-3015, USA.

Department of Pharmaceutics, Virginia Commonwealth University, Richmond, Virginia, USA.

出版信息

Pharm Res. 2015 Oct;32(10):3170-87. doi: 10.1007/s11095-015-1695-1. Epub 2015 May 6.

Abstract

PURPOSE

CFD provides a powerful approach to evaluate the deposition of pharmaceutical aerosols; however, previous studies have not compared CFD results of deposition throughout the lungs with in vivo data.

METHODS

The in vivo datasets selected for comparison with CFD predictions included fast and slow clearance of monodisperse aerosols as well as 2D gamma scintigraphy measurements for a dry powder inhaler (DPI) and softmist inhaler (SMI). The CFD model included the inhaler, a characteristic model of the mouth-throat (MT) and upper tracheobronchial (TB) airways, stochastic individual pathways (SIPs) representing the remaining TB region, and recent CFD-based correlations to predict pharmaceutical aerosol deposition in the alveolar airways.

RESULTS

For the monodisperse aerosol, CFD predictions of total lung deposition agreed with in vivo data providing a percent relative error of 6% averaged across aerosol sizes of 1-7 μm. With the DPI and SMI, deposition was evaluated in the MT, central airways (bifurcations B1-B7), and intermediate plus peripheral airways (B8 through alveoli). Across these regions, CFD predictions produced an average relative error <10% for each inhaler.

CONCLUSIONS

CFD simulations with the SIP modeling approach were shown to accurately predict regional deposition throughout the lungs for multiple aerosol types and different in vivo assessment methods.

摘要

目的

计算流体动力学(CFD)为评估药物气溶胶的沉积提供了一种强大的方法;然而,以往的研究尚未将全肺沉积的CFD结果与体内数据进行比较。

方法

选择用于与CFD预测进行比较的体内数据集包括单分散气溶胶的快速和慢速清除以及干粉吸入器(DPI)和软雾吸入器(SMI)的二维γ闪烁扫描测量。CFD模型包括吸入器、口咽(MT)和上气管支气管(TB)气道的特征模型、代表其余TB区域的随机个体路径(SIPs)以及基于CFD的最新相关性,以预测药物气溶胶在肺泡气道中的沉积。

结果

对于单分散气溶胶,全肺沉积的CFD预测与体内数据一致,在1-7μm的气溶胶尺寸范围内平均相对误差为6%。使用DPI和SMI时,在MT、中央气道(B1-B7分叉)以及中间和外周气道(B8直至肺泡)中评估沉积。在这些区域中,每种吸入器的CFD预测平均相对误差<10%。

结论

采用SIP建模方法的CFD模拟被证明能够准确预测多种气溶胶类型和不同体内评估方法下全肺的区域沉积。

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