Experimental and modeling approaches to determine drug diffusion coefficients in artificial mucus
Ashley C Wynne1, Brandon S Abbott2, Reza Niazi3
1Sealed Air Corporation, 2405 Cascade Pointe Blvd, Charlotte, NC, 28208, USA.
Abstract:
Asthma, usually characterized by inflammation and mucus accumulation, causes restricted airflow and impaired lung function. The physiological and biochemical characteristics of mucus pose a strong barrier for drugs administered orally or via the pulmonary route for asthma treatment. In this study, two drugs commonly employed in the treatment of asthma, theophylline and albuterol, were placed in contact with an artificial mucus layer, measuring their interface concentrations, and modeling the concentration profiles to determine their diffusion coefficients. To monitor the diffusion process, the upper surface of a mucus layer was placed in contact with the drug solutions and the lower mucus surface was in contact with a zinc selenide crystal to allow for time-resolved Fourier transform infrared spectroscopy (FTIR) measurements. FTIR spectra were collected at constant time intervals and monitored for quantitative changes in spectral peaks corresponding to functional groups specific to each of these drugs. Changes in peak heights were correlated to concentration via Beer's Law. Fick's 2nd Law of Diffusion was used along with Crank's trigonometric series solution for a planar semi-infinite sheet to analyze the concentration data and determine diffusion coefficients. Using this method, fitting the experimental data resulted in diffusivity coefficients of D = 6.56 x 10-6 cm2/s for theophylline and D = 4.66 x 10-6 cm2/s for albuterol through artificial mucus. The drug diffusivity coefficients align closely with literature reports, wherein, diffusivity data was obtained experimentally using a rotating-disk apparatus and intrinsic dissolution technique. By coupling analytical and experimentally determined drug diffusion data, this approach provides a fast, non-invasive method for quickly assessing drug diffusion profiles through complex media.
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