摘要
目的 基于质量源于设计(QbD)理念优化黄芪甲苷PLGA纳米粒的处方配比及制备工艺。方法 采用乳化溶剂挥发法制备黄芪甲苷纳米粒。以黄芪甲苷纳米粒的包封率、载药量、粒径大小以及PDI计算总评归一值(OD值)为评价指标,首先应用Plackett-Burman实验设计筛选出对黄芪甲苷纳米粒性质影响显著的工艺变量,然后对筛选出的变量应用星点设计-效应面法进一步优化,并对其进行表征评价,考察纳米粒的体外释药行为。结果 基于Qb D理念,通过星点设计-效应面法对关键工艺参数(CPPs)进行优化,得到的最优处方总投药量为5.03 mg、泊洛沙姆浓度为0.48%、W/O体积比为14.33∶1。经验证黄芪甲苷纳米粒的包封率为(68.86±2.90)%,载药量为(4.78±0.45)%,粒径为(112.87±4.69)nm,PDI为0.134±0.010,ζ电位(-29.77±1.40)m V,且纳米粒呈圆球形,粒子均匀分散,未见粘连聚集,通过体外释放实验得知,纳米粒体外释药规律符合Riger-Peppas释药方程模型。结论 基于Qb D理念,得到了优化模型的产品,符合预期的QTPP质量稳定、可控,精度高,预测效果较好,制备工艺稳定可行。
Objective To optimize the formulation ratio and preparation process of astragaloside IV PLGA nanoparticles based on quality by design(QbD). Methods Astragaloside IV nanoparticles were prepared by emulsification solvent evaporation method.Taking the encapsulation efficiency, drug loading, particle size and PDI calculated overall desirability(OD) of astragaloside IV nanoparticles as evaluation indicators. Plackett-Burman design was used to screen out the process variables that had a significant effect on the properties of astragaloside IV nanoparticles, and then the selected variables were further optimized by central composite designresponse surface methodology, and were characterized and evaluated to investigate the in vitro drug release behavior of nanoparticles.Results Based on QbD, the critical process parameters(CPPs) were optimized by central composite design-response surface methodology, and the optimal prescription dosage was 5.03 mg, the poloxamer concentration was 0.48, and the W/O volume ratio was 14.33:1. It was verified that the encapsulation efficiency of astragaloside IV nanoparticles was(68.86 ± 2.90)%, the drug loading was(4.78 ± 0.45)%, the particle size was(112.87 ± 4.69) nm, the PDI was 0.134 ± 0.010, the ζ was(-29.77 ± 1.40) mV, and the nanoparticles were spherical, the particles were uniformly dispersed, and there was no adhesion and aggregation. Release experiment in vitro showed that the drug release rule of the nanoparticles conformed to the Riger-Peppas model. Conclusion Based on QbD, the product of the optimized model is obtained, which meets the expected QTPP and has stable and controllable quality, high precision, good prediction effect, and stable and feasible preparation process.
作者
李姿锐
王一婷
兰帆
周素华
李雅
LI Zi-rui;WANG Yi-ting;LAN Fan;ZHOU Su-hua;LI Ya(Hunan University of Chinese Medicine,Changsha 410208,China)
出处
《中草药》
CAS
CSCD
北大核心
2022年第15期4678-4686,共9页
Chinese Traditional and Herbal Drugs
基金
湖南省自然科学基金资助项目(2021JJ30495)
湖南省大学生创新创业训练计划项目(2603)
湖南中医药大学中药学一流学科建设项目(4901-0200002006)。
