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3011194 
Journal Article 
Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data 
Tian, G; Hindle, M; Lee, S; Longest, PW 
2015 
1 
Pharmaceutical Research
ISSN: 0724-8741
EISSN: 1573-904X 
32 
10 
3170-3187 
English 
25944585 
WOS:000361720700005 
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. 
airway dosimetry predictions; computational fluid dynamics (CFD); pharmaceutical aerosols; predictions of aerosol deposition; respiratory drug delivery