Pharmaceutical Research

, Volume 32, Issue 10, pp 3170–3187 | Cite as

Validating CFD Predictions of Pharmaceutical Aerosol Deposition with In Vivo Data

  • Geng Tian
  • Michael Hindle
  • Sau Lee
  • P. Worth Longest
Research Paper



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.


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.


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.


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 



One dimensional


Two dimensional


Three dimensional


Airway bifurcation number




Computational fluid dynamics


Chronic obstructive pulmonary disease


Computed tomography


Deposition fraction


Dry powder inhaler




Functional residual capacity


High performance liquid chromatography




Left lower (lung lobe)


Liters per minute


Low Reynolds Number


Metered dose inhaler


Mass median aerodynamic diameter






Next Generation Impactor




Peak inspiratory flow rate


Particle size distribution




Slow-and-deep or standard deviation


Stochastic individual pathway


Softmist inhaler


Single-photon emission computed tomography





Katharina Bormann and Xiangyin Wei are acknowledged for their assistance in measuring the initial size of the Novolizer DPI. Navvab Dalasm is credited with creating the alveolar model shown in Fig. 3 while at VCU. This study was supported by Award U01 FD004570 from the US FDA and Award R01 HL107333 from the National Heart, Lung, and Blood Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the US FDA, the National Heart, Lung, and Blood Institute or the National Institutes of Health.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Geng Tian
    • 1
  • Michael Hindle
    • 2
  • Sau Lee
    • 3
  • P. Worth Longest
    • 1
    • 2
  1. 1.Department of Mechanical and Nuclear EngineeringVirginia Commonwealth UniversityRichmondUSA
  2. 2.Department of PharmaceuticsVirginia Commonwealth UniversityRichmondUSA
  3. 3.Office of Pharmaceutical Quality, Center for Drug Evaluation ResearchUnited States Food and Drug AdministrationSilver SpringUSA

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