响应面法优化氧化槐定碱脂质体的制备及表征
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摘要：
以包封率为评价指标,采用单因素实验和Box-Behnken响应面设计法优化氧化槐定碱脂质体的制备工艺.采用透射电镜、包封率、载药量、Zeta电位、红外光谱、差示扫描量热分析等表征氧化槐定碱脂质体.氧化槐定碱脂质体的最佳制备工艺为:大豆卵磷脂与胆固醇的质量比为10∶3.09、大豆卵磷脂与药物的质量比为10∶1.54、水合时间为1.46 h.氧化槐定碱脂质体的平均粒径为154.1 nm,分散系数为0.329,平均包封率为58.02%(RSD为1.63%),平均载药量为6.27%(RSD为1.52%),Zeta电位为-29.9 mV.经验证最佳制备工艺稳定可行,氧化槐定碱脂质体的外观成类球形、粒径分布较为均匀,混悬液稳定,不宜发生絮凝.
Taking the encapsulation rate as an evaluation index,single factor experiment and Box-Behnken response surface design method were used to optimize the preparation process of oxysophoridine liposomes.The oxysophoridine liposomes was characterized by transmission electron microscopy,particle size,encapsulation efficiency,drug loading,Zeta potential,infrared spectroscopy,and differential scanning calorimetry and so on.The best preparation process of the oxysophoridine liposomes were that the mass ratio of soybean lecithin to cholesterol was 10∶3.09,the mass ratio of soybean lecithin to drug was 10∶1.54,and the hydration time was 1.46 h.The characterization results of oxysophoridine liposomes was that the average particle size was 154.1 nm,the dispersion coefficient was 0.329,the average encapsulation efficiency was 58.02%(RSD 1.63%),the average drug loading was 6.27%(RSD 1.52%),and Zeta potential was-29.9 mV.It has been verified that the optimal preparation process of the oxysophoridine liposomes was stable and feasible.And the characterization of oxysophoridine liposomes shows that the appearance was spherical,the particle size distribution was relatively uniform,the liposomes suspension was stable,and should not be flocculated.
作者：
郭留城 杜利月 冯慧慧 高笑笑 崔凤灵
Guo Liucheng;Du Liyue;Feng Huihui;Gao Xiaoxiao;Cui Fengling(School of Chemistry and Chemical Engineering,Henan Normal University,Xinxiang 453007,China)
机构地区：
betway官方app 化学化工学院
出处：
《betway官方app 学报：自然科学版》 CAS 北大核心 2022年第2期111-120,共10页
Journal of Henan Normal University(Natural Science Edition)
基金：
国家自然科学基金(U1704170) 河南省高等学校青年骨干教师培养计划(2017GGJS286) 校级科研资助项目(2016-S-LMC-12).
关键词：
氧化槐定碱 脂质体 响应面法 表征
oxysophoridine liposomes response surface methodology characterization
分类号：
O657.7 [理学—分析化学]
