Two modelling data analytical methods applied to optimise the preparation of norcantharidin chitosan nanoparticles

Autor:	Yang Liu, Wen-Juan Wang, Qiang Zhang, Xiao-yan Chen, Yong-Yan Bei, Xue-Nong Zhang, Wei Zhang, Jing-Yu Xu
Rok vydání:	2010
Předmět:	Materials science Norcantharidin Artificial neural network Biomedical Engineering Bioengineering Regression analysis Chitosan nanoparticles Chitosan chemistry.chemical_compound chemistry Linear regression General Materials Science Particle size Biological system Nonlinear regression
Zdroj:	Journal of Experimental Nanoscience. 5:271-284
ISSN:	1745-8099 1745-8080
DOI:	10.1080/17458080903513284
Popis:	In our study, the non-linear regression model and artificial neural networks (ANNs) were used to optimise the preparation of the loading norcantharidin chitosan nanoparticles (NPs) by ionic cross-linkage. Two major indexes, the particle size and the entrapment efficiency of the drug vehicles were synchronously optimised according to the normalised value calculated referring to the weights of the indexes and factors. For the purpose, a multiple regression model was constructed for fitting several preparation factors, including the low molecular weight of chitosan (LCS), sodium tripolyphosphate (TPP) concentrations and the temperature of the ionic cross-linkage reaction. Each of the level values in the factors was arranged using the L9(34) table and their linear weighted sum of the normalised value was taken as optimised object. A back-propagation (BP) network (3 × 7 × 2) in ANNs was created and trained for further checking the optimal results and the trained network was applied to simulate the experiment s...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7ccd465ed4fca1fffd91536052a53bd7 https://doi.org/10.1080/17458080903513284 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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