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Two modelling data analytical methods applied to optimise the preparation of norcantharidin chitosan nanoparticles
Zhang, Wei1; Liu, Yang1; Chen, Xiao-Yan1; Bei, Yong-Yan1; Xu, Jing-Yu1; Wang, Wen-Juan1; Zhang, Xue-Nong1; Zhang, Qiang2
关键词Chitosan Nanoparticles Non-linear Regression Artificial Neural Networks
刊名JOURNAL OF EXPERIMENTAL NANOSCIENCE
2010
DOI10.1080/17458080903513284
5期:3页:271-284
收录类别SCI
文章类型Article
WOS标题词Science & Technology
类目[WOS]Chemistry, Multidisciplinary ; Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Physics, Applied
研究领域[WOS]Chemistry ; Science & Technology - Other Topics ; Materials Science ; Physics
关键词[WOS]PH-SENSITIVE NANOPARTICLES ; CYCLOSPORINE-A ; DELIVERY ; DESIGN ; EXTRACTION ; SYSTEMS ; PROTEIN ; BIOAVAILABILITY ; MICROSPHERES ; INHIBITOR
英文摘要

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 x 7 x 2) in ANNs was created and trained for further checking the optimal results and the trained network was applied to simulate the experiment system and screen the optimal conditions. Finally, when the weights of temperature, particle size and entrapment efficiency were 0.1, 0.4 and 0.5, respectively, the best preparation condition of NPs was obtained as 131 +/- 7 nm of particle size and 45.12% of entrapment efficiency at 40 degrees C.

语种英语
WOS记录号WOS:000279451800008
项目编号2006BAI09B00 ; 07C26223201333 ; BS2005022 ; JHB05-46 ; H200630
资助机构National Key Technology RD Program ; Innovation Fund of Medium or Small Science and Technology Enterprises ; National Science and Technology Ministry ; Social Development Foundation of Jiangsu Province ; Department of Education of Jinagsu Province ; Health Department of Jinagsu Province
引用统计
被引频次:6[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.bjmu.edu.cn/handle/400002259/51280
专题北京大学药学院_药剂学系
作者单位1.Soochow Univ, Coll Pharm, Suzhou 215123, Peoples R China
2.Peking Univ, Sch Pharmaceut Sci, Dept Pharmaceut, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Wei,Liu, Yang,Chen, Xiao-Yan,et al. Two modelling data analytical methods applied to optimise the preparation of norcantharidin chitosan nanoparticles[J]. JOURNAL OF EXPERIMENTAL NANOSCIENCE,2010,5(3):271-284.
APA Zhang, Wei.,Liu, Yang.,Chen, Xiao-Yan.,Bei, Yong-Yan.,Xu, Jing-Yu.,...&Zhang, Qiang.(2010).Two modelling data analytical methods applied to optimise the preparation of norcantharidin chitosan nanoparticles.JOURNAL OF EXPERIMENTAL NANOSCIENCE,5(3),271-284.
MLA Zhang, Wei,et al."Two modelling data analytical methods applied to optimise the preparation of norcantharidin chitosan nanoparticles".JOURNAL OF EXPERIMENTAL NANOSCIENCE 5.3(2010):271-284.
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