复方天宁滴丸制备工艺效应面优化模型的研究

Research of Tianning Dropping Pills Preparation by Response Surface Methodology Optimization Model

关键词:  复方天宁滴丸  星点设计-效应面优化法  总评归一值

Key words:  compound tianning dripping pills  central composite design-response surface methodology(CCD-RSM)  overall desirability

摘要:

目的 应用星点设计-效应面法优化复方天宁滴丸制备工艺。方法 以PEG6000和棕榈山梨坦(司盘40)为联合基质，以药物的质量分数及PEG6000质量分数为自变量，以丸重差异、溶散时限以及一定时间的阿魏酸溶出度为因变量，对试验数据进行多元线性模型和二项式模型拟合，得出最佳数学模型，绘制效应图和等高线图，再根据效应图优选最佳条件。结果 二项式模型相关系数优于多元线性模型，复相关系数为0.970，复方天宁滴丸最佳处方为药物质量分数23%，PEG6000质量分数47%，模型的理论预测值与实测值偏差较小，模型具有良好的预测性。结论 星点设计-效应面法建立的模型预测性良好，可用于对复方天宁滴丸制备工艺的优化。

Abstract:

OBJECTIVE To optimize the formulations of compound Tianning dropping pills by central composite design- response surface methodology. METHODS Dropping pill was prepared through melting method with PEG6000 and S40 as combined carrier. Independent variables were drugs content and PEG6000 content, while dependent variables were weight variation of pills and the ferulic acid dissolution rate of definite time. Software was used to fit multivariate linear equation and second-order polynomial equation for experimental data. Response surface and contour plot were delineated according to bestfit mathematic models by software, and the optimum formulation was selected by response surface. RESULTS Quadratic multinomial model was better than multivariate linear model, and the regression coefficient was 0.970. The best prescription of compound Tianning dropping pill was that drugs content was 23%, while PEG6000 content was 45%. The bias between the observed and predicted values of the optimum process was negligible, indicating the high predictability of the model. CONCLUSION The model established by central composite design-response surface methodology and SPSS software is accurate for prediction and can be used to optimize the preparation process of Tianning dropping pills.