Mechanisms of Pharmaceutical Aerosol Deposition in the Respiratory Tract

The deposition of inhaled aerosol particles in the human respiratory tract is due to the mechanisms of inertia impaction, Brownian diffusion, and gravitational settling. A theory is developed to predict the particle deposition and its distribution in human respiratory tract for any breathing condition. A convection-diffusion equation for the particle concentration with a loss term is used to describe the transport and deposition of particles. In this equation, an apparent diffusion coefficient due to the velocity dispersion in the lung is present and found to be the dominant diffusion mechanism for the cases considered here. Expressions for deposition by various mechanisms are also derived. The governing equation is solved numerically with Weibel's lung model A. The particle concentration at the mouth is calculated during washin and washout and compared favorably with experimental recordings for 0.5-mum diameter di(2-ethylhexyl) sebacate particles. The total deposition in the lung for particle size ranging from 0.05 to 5 mum is also computed for a 500-cm-3 tidal volume and 15 breaths/min. The results in general agree with recent measurements of Heyder et al. However, a particle size of minimum deposition is found to exist theoretically near 0.3 mum.

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MIST THERAPY RECONSIDERED; AN EVALUATION OF THE RESPIRATORY DEPOSITION OF LABELLED WATER AEROSOLS PRODUCED BY JET AND ULTRASONIC NEBULIZERS

PEDIATRICS ◽

10.1542/peds.43.5.799 ◽

1969 ◽

Vol 43 (5) ◽

pp. 799-808

Author(s):

Jack Wolfsdorf ◽

David L. Swift ◽

Mary Ellen Avery

Keyword(s):

Standard Deviation ◽

Respiratory Tract ◽

Propylene Glycol ◽

Lower Respiratory Tract ◽

Aerosol Deposition ◽

Geometric Standard Deviation ◽

Upper Respiratory Tract ◽

Nasal Breathing ◽

Upper Respiratory ◽

Mass Median

Aerosol deposition in the upper and lower respiratory tract using technetium-labelled water aerosol, produced by jet and ultrasonic nebulizers, with and without 10% propylene glycol, was examined under conditions of nasal, normal mouth, and tube breathing in 15 normal adults. With nasal breathing, 91.5% (± 5.5) and 83.2% (± 6.3) of the mass of the aerosol produced by the jet and ultrasonic nebulizers, respectively, was deposited in the upper respiratory tract. Similar fractional depositions were observed with the addition of 10% propylene glycol. When breathing was carried out via a mouth tube, 43% to 59% of the mass of the aerosol produced by the nebulizers was deposited in the upper respiratory tract. The mass median diameters of the available aerosols produced by the jet and ultrasonic nebulizers were 6.0 µ (geometric standard deviation = 2.5) and 2.8 µ (geometric standard deviation = 2.1), respectively; the densities of the aerosols produced were 8 and 34 µl/liter air. With nasal or normal mouth breathing, the volume of water, in aerosol form, that could be deposited per 24 hours in the lower respiratory tract of an adult was calculated to be about 6 ml and 49 ml for the jet and ultrasonic nebulizer, respectively.

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Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates

Atmosphere ◽

10.3390/atmos11020137 ◽

2020 ◽

Vol 11 (2) ◽

pp. 137 ◽

Cited By ~ 3

Author(s):

Vu Khac Hoang Bui ◽

Ju-Young Moon ◽

Minhe Chae ◽

Duckshin Park ◽

Young-Chul Lee

Keyword(s):

Respiratory Tract ◽

Particle Deposition ◽

Computational Models ◽

Aerosol Particles ◽

Three Dimensional ◽

Aerosol Deposition ◽

Research Area ◽

Human Respiratory Tract

The measurement of deposited aerosol particles in the respiratory tract via in vivo and in vitro approaches is difficult due to those approaches’ many limitations. In order to overcome these obstacles, different computational models have been developed to predict the deposition of aerosol particles inside the lung. Recently, some remarkable models have been developed based on conventional semi-empirical models, one-dimensional whole-lung models, three-dimensional computational fluid dynamics models, and artificial neural networks for the prediction of aerosol-particle deposition with a high accuracy relative to experimental data. However, these models still have some disadvantages that should be overcome shortly. In this paper, we take a closer look at the current research trends as well as the future directions of this research area.

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