Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106634
Title: Empirical modeling of the fine particle fraction for carrier-based pulmonary delivery formulations
Authors: Pacławski, Adam
Szlęk, Jakub
Lau, Raymond
Jachowicz, Renata
Mendyk, Aleksander
Keywords: DRNTU::Science::Medicine
Issue Date: 2015
Source: Pacławski, A., Szlęk, J., Lau, R., Jachowicz, R., & Mendyk, A. (2015). Empirical modeling of the fine particle fraction for carrier-based pulmonary delivery formulations. International journal of nanomedicine, 10, 801-810.
Series/Report no.: International journal of nanomedicine
Abstract: In vitro study of the deposition of drug particles is commonly used during development of formulations for pulmonary delivery. The assay is demanding, complex, and depends on: properties of the drug and carrier particles, including size, surface characteristics, and shape; interactions between the drug and carrier particles and assay conditions, including flow rate, type of inhaler, and impactor. The aerodynamic properties of an aerosol are measured in vitro using impactors and in most cases are presented as the fine particle fraction, which is a mass percentage of drug particles with an aerodynamic diameter below 5 µm. In the present study, a model in the form of a mathematical equation was developed for prediction of the fine particle fraction. The feature selection was performed using the R-environment package “fscaret”. The input vector was reduced from a total of 135 independent variables to 28. During the modeling stage, techniques like artificial neural networks, genetic programming, rule-based systems, and fuzzy logic systems were used. The 10-fold cross-validation technique was used to assess the generalization ability of the models created. The model obtained had good predictive ability, which was confirmed by a root-mean-square error and normalized root-mean-square error of 4.9 and 11%, respectively. Moreover, validation of the model using external experimental data was performed, and resulted in a root-mean-square error and normalized root-mean-square error of 3.8 and 8.6%, respectively.
URI: https://hdl.handle.net/10356/106634
http://hdl.handle.net/10220/25049
ISSN: 1178-2013
DOI: 10.2147/IJN.S75758
Schools: School of Chemical and Biomedical Engineering 
Rights: © 2015 Pacławski et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information on how to request permission may be found at: http://www.dovepress.com/permissions.php
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

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