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中心复合设计法优化盐酸环丙沙星海藻酸钠-壳聚糖双层膜的处方 被引量:4

Application of central composite designs to the preparation of ciprofloxacin hydrochloride loaded alginate-chitosan bi-layer membrane
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摘要 目的采用中心复合设计法优化盐酸环丙沙星海藻酸钠-壳聚糖双层膜的处方。方法考察甘油质量浓度、交联剂CaCl2质量浓度和交联时间对双层膜单位面积的载药量,吸水率,抗张强度,断裂伸长率,水蒸气透过率,药物释放12、24、48 h累积释放度8个指标的影响。用多元线性方程和二次多项式描述各指标及总评"归一值"和3个影响因素之间的数学关系,根据总评"归一值"的最佳数学模型描绘效应面,选择最佳处方,并进行预测分析。结果 3个影响因素和8个评价指标及总评"归一值"之间存在定量关系。优选的最佳条件为甘油质量浓度为47.1 g.L-1,CaCl2质量浓度为95.4 g.L-1,交联时间为4.63 min。优化处方各指标的预测值和目标值接近。结论中心复合设计较好的完成了载药双层膜的处方优化,所建立的模型预测性良好。 Objective To design and optimize the formulation by a central composite design/response surface methodology. Methods The effect of formulation variables (glycerin concentration, CaCI: concentration and crosslinking time)on a number of response variables was systemically investigated. The response variables were drug loading, water uptake capacity, water vapor transmission rate, tensile strength, breaking elongation,cumulative drug release at 12 h, 24 h and 48 h. A desirability function that combines these eight response variables was constructed. A second-order polynomial equation was fitted to the data, and the resulting equation was used to predict the responses in the optimal region. Results All the investigated response variables were found to be highly dependent on the formulation variables. It was found that optimum overall desirability of the drug-loaded composite membranes could be obtained at 47.1 g·L^-1 of glycerin concentra- tion, at 95.4 g·L^-1 of concentration of CaC12 solution, and at 4.63 min of crosslinking time. The experimental values of the response variables highly agreed with the predict values. Conclusions Central composite design is successfully used to optimize the preparation of alginate/chitosan composite membrane containing ciprofloxacin hydrochloride.
出处 《沈阳药科大学学报》 CAS CSCD 北大核心 2011年第2期99-104,134,共7页 Journal of Shenyang Pharmaceutical University
关键词 盐酸环丙沙星 海藻酸钠-壳聚糖双层膜 星点设计 效应面 优化 ciprofloxacin hydrochloride alginate-chitosan composite membrane central composite design response surface optimization
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