Abstract

Inhalation medicinal aerosol and biological aerosol risk assessment are the current motivation for deposition models to be developed. Inhalation aerosols have been around for many years for the treatment of asthma and other respiratory ailments in which the aerosols targeted the upper airways. Current research is focused to target the alveolar sacs due to their vast surface area for drug and gene delivery. Targeting the alveolar sacs Corkery (2000) requires a slow and deep breathing pattern for maximum deposition at the alveolar units. Also the particles must be fairly small (1-3 µm) to avoid deposition by impaction. Gautam et al. (2003), states that aerosol inhalation therapy has the following advantages: a greater surface area to absorb and sediment drugs and genes, the absorption is immediate, there is low systemic toxicity, and the delivery of the drug is a non-invasive procedure. The authors' foresee inhalation medicine coming into practice in the near future. A proven and effective case is the delivery of insulin formulation via an inhalation device. Through inhalation of insulin, patients will not have to tolerate the constant injection of insulin thus improving their obedience in taking their insulin devotedly.

Biological aerosol risk assessment is another topic that warrants deposition modeling in the lung. According to Douwes et al. (2003), the occupational environment is producing potent bio-aerosols that lead to infectious diseases, acute toxic effects, allergies and cancer within people exposed to these aerosols. The authors cite examples of industries that are producing these bio-aerosols, such as the cotton industry, farming, waste and compost industry, and the automotive industry, etc. The main focus is to assess these industries and the bio-aerosols that they produce in a quantitative way. The authors' note that these assessments of bio-aerosols have mainly been qualitative or semi-quantitative at best in research and stress that there needs to be more quantitative analysis on the bio-aerosol production and risk assessment, so that proper care and caution can be taken in the future.

There are significant gaps in information completeness concerning modeling particulate deposition in diseased lungs. The gaps in information stem from inaccurate or vague results in quantification of the geometric and dynamic parameters that deviate respiratory ailments from a normal individual, also, there is lack of computer models that describe the different respiratory ailments. This former idea is a necessity for advancement of a particular problem. Computer models reflect a compilation of knowledge on a particular subject that produces an end result that can be verified readily by field tests.

The goal of this research was two-fold. First objective were to perform a literature search that summarized the current literature on experimental deposition data, pulmonary function test data, and airway modifications due to asthma and COPD. Second, the separate modules of the computer routine will predict deposition of inhaled particles of varying sizes in a symptomatic asthmatic case (COPD data from literature did not yield enough quantitative data to make modifications). The inputs consist of breathing patterns, lung geometry, and particle concentration and distribution. The inputs are then used in conservation equations and deposition mechanisms to describe how the particles will move throughout the region. Outputs are in the form of mass deposition fraction [%], deposition efficiency, and average deposition per generation.

Overall the model was successful in predicting the intuition one would have in comparing deposition amounts in asthma versus healthy cases. There was more total deposition of particles for every particle size in the symptomatic asthma cases relative to the normal case specifically as particle size increased. The increased deposition was primarily due to the impaction deposition mechanism for larger particles sizes, specifically 5 µm and 10 µm particle sizes.

This work was supported by a grant from the Phillip Morris External Research Foundation.

Library of Congress Subject Headings

Respiratory therapy--Evaluation; Respiratory therapy--Computer simulation; Particles--Measurement; Asthma--Treatment--Evaluation; Asthma--Treatment--Computer simulation

Publication Date

5-2005

Document Type

Thesis

Student Type

Graduate

Degree Name

Mechanical Engineering (MS)

Department, Program, or Center

Mechanical Engineering (KGCOE)

Advisor

Risa J. Robinson

Advisor/Committee Member

Elizabeth A. DeBartolo

Advisor/Committee Member

Mark Kempski

Comments

Physical copy available from RIT's Wallace Library at RC735.I5 D4 2005

Campus

RIT – Main Campus

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