Research Papers

Optimal Drug-Aerosol Delivery to Predetermined Lung Sites

[+] Author and Article Information
Clement Kleinstreuer1

Department of Mechanical and Aerospace Engineering and Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695; University of North Carolina, Chapel Hill, NC 27599ck@eos.ncsu.edu

Zhe Zhang

Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695


Corresponding author.

J. Heat Transfer 133(1), 011002 (Sep 27, 2010) (12 pages) doi:10.1115/1.4002224 History: Received March 31, 2010; Revised April 28, 2010; Published September 27, 2010; Online September 27, 2010

This review summarizes computer simulation methodologies of air-particle flow, results of drug-aerosol transport/deposition in models of the human respiratory system, as well as aspects of drug-aerosol targeting and associated inhalation devices. After a brief introduction to drug delivery systems in general, the required modeling and simulation steps for optimal drug-aerosol delivery in the lung are outlined. Starting with medical imaging and file conversion of patient-specific lung-airway morphologies, the air-particle transport phenomena are numerically solved for a representative inhalation flow rate of Qtotal=30l/min. Focusing on microspheres and droplets, the complex airflow and particle dynamics, as well as the droplet heat and mass transfer are illustrated. With this foundation as the background, an overview of present inhaler devices is presented, followed by a discussion of the methodology and features of a new smart inhaler system (SIS). With the SIS, inhaled drug-aerosols can be directly delivered to any predetermined target area in the human lung.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Schematics of the human respiratory system (6)

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Figure 2

Example of airflow structures in a combined human nasal-oral-tracheobronchial airway model at a constant inspiratory flow rate of Qnasal,in=15 l/min and Qoral,in=15 l/min. The local mean velocities (ulocal,m) of slices A, B, and C are 2.5 m/s, 2.18 m/s, and 2.66 m/s, respectively.

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Figure 3

Example of air temperature distributions in a combined human nasal-oral-tracheobronchial airway model at an inlet temperature of 25°C and a constant inspiratory flow rate of Qnasal,in=15 l/min and Qoral,in=15 l/min

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Figure 4

Variations of cross-sectional averaged relative humidity with Qin=30 l/min in (a) the oral airway model and (b) the bifurcation airway models G0–G3. Adapted from Zhang (32).

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Figure 5

Comparison of nondirectional (a) and more targeted (b) drug-aerosol delivery

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Figure 6

(a) Controllable particle distributions in the upper airway models when releasing from a given position at mouth inlet with Qin=8 l/min and dp=7 μm. The capture efficiency of particles after G3.1 increases from 12.4% (normal, nondirectional inhalation) to 100% (targeted inhalation). (b) Comparison between computational and experimental measurements of particle paths through the trachea as a function of release point.

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Figure 7

Regions of optimal particle-release positions for targeting at the mouth inlet (or inhaler exit)

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Figure 8

Schematic of inhalation flow control system (left panel) and modulated inhalation flow waveform (right panel Qm should be less than 8 l/min to maintain laminar flows)

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Figure 9

Illustration of autonomous SIS design (patent pending): slice view with components (left) and air flow pattern with co-flow splitting for aerosolizer supply (right)




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