Optimization of a doxycycline hydroxypropyl-β-cyclodextrin inclusion complex based on computational modeling

查看全文 作　　者：Zhouhua [1,2]Wang;Zixin [1,3]He;Lei [4]Zhang;Haohao [1]Zhang;Meimei [1]Zhang;Xinguo [1]Wen;Guilan [1]Quan;Xintian [1]Huang;Xin [1]Pan;Chuanbin [1,2]Wu

机构地区：[1]School of Pharmaceutical Sciences,Sun Yat-sen University,Guangzhou 510006,China;[2]Research and Development Center of Pharmaceutical Engineering,Sun Yat-sen University,Guangzhou 510006,China;[3]Zhong Yi Pharmaceutical Company Ltd.,Guangzhou 510530,China;[4]School of Mathematics&Computational Sciences,Sun Yat-sen University,Guangzhou 510275,China

出　　处：《Acta Pharmaceutica Sinica B》索引2013年第3卷第2期,共10页

基　　金：supported by the National Natural Science Foundation of China(Grant No.81173002);the National Science&Technology Pillar Program(Grant No.2012BAI35B02);the International Cooperation and Exchange Program of China(Grant No.2008DFA31080). 摘　　要：To prepare a stable complex of doxycycline(Doxy)and hydroxypropy-β-cyclodextrin(HP-β-CD)for ophthalmic delivery,the optimum formulation and preparation conditions were investigated using response surface methodology(RSM),artificial neural network(ANN)and support vector machine(SVM)modeling.The molar ratios of HP-β-CD/Doxy and Mg^(2+)/Doxy,inclusion time and temperature were selected as independent variables (X_(1)-X_(4)) and inclusion efficiency and stability of the Doxy-HP-β-CD complex were selected as dependent(response)variables(Y_(1) and Y_(2)).The optimal formulation predicted by genetic algorithm(GA)combined with the models was characterized by microscopy and nuclear magnetic resonance spectrometry,and the stability of Doxy in the complex was evaluated.The highest values of Y_(1) and Y_(2) were obtained using an ANN model combined with GA which predicted the values of X_(1)-X_(4) to be 4,10.8,12 h and 25℃,respectively.The modeling and optimization results indicated that a feed-forward back-propagation ANN with one hidden layer and 10 hidden units showed better fitting to both responses compared to the RSM and SVM models.GA proved to be an efficient tool in multiobjective optimization of a pharmaceutical formulation. 关键词：DOXYCYCLINE Hydroxypropy-β-cyclo-dextrin Response surface methodology Artificial neural network Support vector machine Genetic algorithm

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Optimization of a doxycycline hydroxypropyl-β-cyclodextrin inclusion complex based on computational modeling

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