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星点设计-效应面法优化水飞蓟素滴丸的制备工艺
引用本文:陈伟,夏红,吴伟.星点设计-效应面法优化水飞蓟素滴丸的制备工艺[J].医学教育探索,2005(5):679-683.
作者姓名:陈伟  夏红  吴伟
作者单位:上海市药品和医疗器械审评中心 上海200021 (陈伟),复旦大学药学院 上海200032 (夏红),复旦大学药学院 上海200032(吴伟)
摘    要:目的采用固体分散技术将水飞蓟素制成滴丸,以增加其溶出速度,提高生物利用度。以星点设计-效应面优化法对制备工艺进行优化,筛选最佳处方。方法以Po loxam er 188的用量及药物的质量分数为考察因素,崩散时间以及一定时间的溶出度为指标,采用多元线性回归及二次和三次多项式拟合建立指标与考察因素之间的数学关系,根据最佳数学模型描绘效应面,再根据效应面优选最佳条件。结果三次多项式是描述指标与因素之间的最佳模型,r=0.998。最佳处方滴丸的崩散时间及溶出度的理论预测值与实测值偏差较小,模型具有良好的预测性。60 m in溶出度为普通片剂的19倍。结论水飞蓟素制成滴丸后溶出速度显著提高,星点设计-效应面优化法可以很好地应用于处方筛选。

关 键 词:水飞蓟素  滴丸  固体分散体  星点设计  效应面优化法

Optimized preparation of Silymarin Dropping Pill by a central composite design-response surface method
CHEN Wei,XIA Hong,WU Wei.Optimized preparation of Silymarin Dropping Pill by a central composite design-response surface method[J].Researches in Medical Education,2005(5):679-683.
Authors:CHEN Wei  XIA Hong  WU Wei
Institution:CHEN Wei~,XIA Hong~,WU Wei~
Abstract:Objective Using solid dispersion technique to prepare Silymarin Dropping Pill to accelerate dissolution and to improve bioavailability. A central composite design-response surface method was employed to select the optimum formulations. Methods Independent variables were Poloxamer 188 content and silymarin content, while dependent variables were disintegrating time and percent of silymarin dissoluted at a definite time. Linear, two and three order quadratic models were used to estimate the relationship between independent and dependent variables. Response surfaces were delineated according to best-fit mathematic models and optimum formulations were selected there from. Prediction was carried out through comparing the observed and predicted values. Results Three order quadratic equation was the best-fitted mathematic models to describe the relationship between dependent and independent variables, with a regression coefficient of 0.998. Bias between observed and predicted values of disintegrating time and dissolution percentage of optimum formulation dropping pill were negligible, indicating the high predictability of the fit models. Percent dissolution of Silymarin Dropping Pill at 60 min was 19 times as that of conventional tablets. Conclusion Dissolution speed of silymarin can be effectively improved through incorporating into dropping pills. It shows that the optimum mathematic model is highly predictive. The central composite design-response surface method can be fairly used in formulation screening.
Keywords:silymarin  dropping pill  solid dispersion  central composite design (CCD)  response surface method (RSM)  
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