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为了更好的利用正交实验的信息,模糊分析法作为新的统计方法应用于优化脂质体的制备,对评价指标综合考虑获得最优制备条件.设计正交实验通过逆相蒸发法制备脂质体,选择粒径、包封率和物理稳定性作为脂质体质最的评价指标,通过直观分析、方差分析和模糊分析对结果进行处理,由直观分析和模糊分析获得最佳制备条件,再由验证实验比较各方案的优劣.通过模糊分析法,得到了正交实验中所有因素不同水平可能组合实验的全部结果,在综合考虑各个评价指标的情况下得到最佳处方.直观分析和模糊分析的结果并不相同,通过验证实验结果表明模糊分析法更具有优势.与传统方法相比,模糊分析方法预测了各因素与水平全部搭配实验的结果,借助计算机提供比直观分析法与方差分析方法更多的信息,消除了实验范围内的盲区,对处方的优化和筛选具有更好的指导性.“,”A new statistical method, the fuzzy analytical method, was introduced in the optimization processes ofliposome preparation. It took the full advantage of the information from orthogonal experiments to obtain the optimal liposome preparation conditions by considering all the evaluation indexes. Liposomes were made by the modified reverse-phase evaporation method and the properties of liposomes including size, encapsulation efficiency and physical stability were selected as the evaluation indexes to indicate the quality of liposomes. The experimental data of these properties were analyzed by three different methods including direct observation, variance analysis and fuzzy analytical method. The optimal preparation conditions obtained from these methods were validated with further experiments. The results of all possible combinations of levels for all factors in orthogonal experiments were acquired by the fuzzy analytical method. All evaluation indexes were taken into account and the optimal preparation condition was obtained. The optimal preparation conditions from direct observation and fuzzy analytical method were different and further validation studies indicated that the optimal conditions obtained from the fuzzy analytical method were in agreement with that from traditional statistical analysis. Fuzzy analytical method avoided the problem resulted from the traditional method, in which different levels of the same factor were obtained when considering different evaluation indexes. More information could be obtained from the fuzzy analytical method and the blind area within the experimental range was eliminated. As a result, fuzzy analytical method can be applied in the optimization processes of liposome preparation.