Carrier optimization of pulmonary powder systems with using computational intelligence tools
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- @Article{PACLAWSKI:2018:PT,
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author = "Adam Paclawski and Jakub Szlek and
Thi Quynh Ngoc Nguyen and Raymond Lau and Renata Jachowicz and
Aleksander Mendyk",
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title = "Carrier optimization of pulmonary powder systems with
using computational intelligence tools",
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journal = "Powder Technology",
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volume = "329",
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pages = "76--84",
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year = "2018",
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keywords = "genetic algorithms, genetic programming, Particles
optimization, Pulmonary delivery, Surface roughness
analysis, Empirical modeling",
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ISSN = "0032-5910",
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DOI = "doi:10.1016/j.powtec.2018.01.041",
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URL = "http://www.sciencedirect.com/science/article/pii/S0032591018300469",
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abstract = "Efficient delivery of drug particles to the
respiratory tract determines therapeutic efficiency of
pulmonary drugs. Only particles with an aerodynamic
diameter (dae) below five micrometers ( ) deposit in
deep lungs. However fine particles, because of their
cohesive nature, frequently cause difficulties related
to the manufacturing process and stability of the
product. This study is focused on the optimization of
carriers for pulmonary drug delivery systems with the
use of empirical models. Advanced computational
intelligence tools were applied to produce a
mathematical formula able to predict fine particle
fraction (FPF) for a particular formulation. FPF is a
mass percentage of drug particles with an aerodynamic
diameter below 5a . The best model was characterized by
normalized root mean squared error (NRMSE) below
8percent and R2a =a 0.85. The goal of the in silico
optimization was to find the possible directions of
carrier modification in order to maximize FPF. Obtained
results were applied to the laboratory experiments and
resulted in the two new formulations with bovine serum
albumin (BSA) as a model drug. Experimental results
confirmed the model predictions, and the formulation
composed of the carrier with higher bulk density and
surface skewness resulted in greater FPF value. The
presented work is an example of computational
intelligence tools implementation and particles surface
assessment based on SEM images in design of the
decision support systems for the development of
pulmonary powder formulations",
- }
Genetic Programming entries for
Adam Paclawski
Jakub Szlek
Thi Quynh Ngoc Nguyen
Raymond Lau
Renata Jachowicz
Aleksander Mendyk
Citations