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...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.展开更多
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).
文摘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.
