中文摘要：

目的采用星点设计优化洛伐他汀-聚（乳酸-羟基乙酸）共聚物[poly（lactic-co-glycolic acid）,PLGA]纳米粒的制备工艺。方法采用纳米沉淀法制备纳米粒,以药物在有机相中的浓度、水相与有机相的体积比、PLGA与药物的用量比为自变量,以载药量、包封率和药物利用率为因变量,计算＂总评归一值＂,根据星点设计原理进行试验安排,对结果分别进行多元线性回归和二项式拟合,效应面法选取最佳工艺条件进行预测分析。结果各指标与＂总评归一值＂的二项式拟合方程均优于多元线性回归方程,根据优化工艺制备的洛伐他汀-PLGA纳米粒的载药量、包封率和药物利用率分别为（1.70±0.09）%、（86.83±1.75）%和（17.48±0.52）%,纳米粒平均粒径为122 nm,各指标实测值与预测值偏差较小。结论星点设计可用于洛伐他汀-PLGA纳米粒制剂处方的优化,所建立的数学模型预测性良好。

英文摘要：

Objective To optimize the preparation of lovastatin-poly（lactic-co-glycolic acid）（PLGA） nanoparticles by central composite design.Methods The nanoparticles were prepared by nanoprecipitation method,the effects of three independent variables included concentration of lovastatin in acetone,weight ratio of PLGA to lovastatine and volume ratio of water to acetone.Response variables selected in the research were drug loading,entrapment efficiency and recovery of drug.The data were transformed into desirability.Overall desirability（OD）was calculated from the geometric mean of the three desirability of each formulation.The second-order polynomial and linear equations were fitted to the response variables and data of overall desirability.The resulting equation of overall desirability was used to produce 3-D response surface graphs,through which optimal formulation were predicted.Results The result shows that the second-order polynomial equations were superior to those of the linear ones.Three optimal formulations were prepared according to the optimal experimental conditions,the drug loading,entrapment efficiency and recovery of drug were（1.70±0.09）%,（86.83±1.75）% and（17.48±0.52）%,respectively,the particle size was 122 nm.The observed values agreed well with model predicted values.Conclusions Central composite design-response surface methodology can be used to optimize the formulation of lovastatin-loaded PLGA nanoparticle and the estimation of the established model is perfect.