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HERO ID
3011194
Reference Type
Journal Article
Title
Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data
Author(s)
Tian, G; Hindle, M; Lee, S; Longest, PW
Year
2015
Is Peer Reviewed?
1
Journal
Pharmaceutical Research
ISSN:
0724-8741
EISSN:
1573-904X
Volume
32
Issue
10
Page Numbers
3170-3187
Language
English
PMID
25944585
DOI
10.1007/s11095-015-1695-1
Web of Science Id
WOS:000361720700005
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.
Keywords
airway dosimetry predictions; computational fluid dynamics (CFD); pharmaceutical aerosols; predictions of aerosol deposition; respiratory drug delivery
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