基于CCD-RSM联用D-最优混料设计优化抗下肢静脉血栓颗粒制剂工艺的研究
Optimization of Preparation Technology of Anti Lower Limb Venous Thrombosis Granules by CCD-RSM Combined with D-Optimal Mixture Design
仲瑞雪 1程子为 2杨曼宁 2唐雨 2万军 2吴传红 1段小云1
作者信息
- 1. 四川省骨科医院,四川 成都 610041
- 2. 西南交通大学 生命科学与工程学院,四川 成都 610031
- 折叠
摘要
目的 采用星点设计-效应面法(CCD-RSM)联用D-最优混料设计,优化抗下肢静脉血栓颗粒的制剂工艺.方法 以溶媒用量、煎煮时间为主要考察因素,以有效成分丹酚酸B和多糖含量及干膏收率的总评归一值(OD)为评价指标,采用CCD-RSM确定最佳提取工艺;以颗粒吸湿率为评价指标,结合溶化性、成型率、休止角等,利用D-最优混料设计优选最佳成型工艺.结果 最佳提取工艺:采用8倍量水提取2次,每次100 min.成型工艺为浸膏与辅料比例1:2,辅料间比例为可溶性淀粉:糊精:蔗糖=0.452:0.518:0.030.结论 优选的制剂工艺条件稳定、可行,可为抗下肢静脉血栓颗粒的生产提供依据.
Abstract
Objective To optimize the preparation process of Anti Lower Limb Venous Thrombosis Granules using central composite design(CCD)-response surface methodology(RSM)combined with D-optimal mixture design.Methods Taking the solvent dosage and decoction time as the main investigation factors and using the normalized value(OD)of the contents of salvianolic acid B and polysaccharide and the yield of dry extract as the evaluating indicator,the CCD-RSM was used to determine the optimal extraction process.Using the hygroscopicity,solubility,formability of particles and angle of repose as the evaluating indicator,the D-optimal mixture design was used to investigate the optimal forming process.Results The optimal extraction process was as follows:the material was extracted twice with 8 times of solvent,100 min for each time.The optimal forming process was as follows:the ratio of the extract to the excipients was 1:2,and the ratio of the excipients was soluble starch:dextrin:sucrose=0.452:0.518:0.030.Conclusion The optimized preparation process is stable and feasible,which can provide a basis for the production of Anti Lower Limb Venous Thrombosis Granules.
关键词
抗下肢静脉血栓颗粒/星点设计-效应面法/D-最优混料设计/提取工艺/成型工艺Key words
Anti Lower Limb Venous Thrombosis Granules/CCD-RSM/D-optimal mixture design/preparation technology/extraction process引用本文复制引用
基金项目
四川省科技计划项目(2022NSFSC1598)
中央高校基本科研业务费专项资金(2022106130081)
四川省科技计划项目(2021YFS0257)
四川省骨科医院临床研究面上项目(2021MS03)
出版年
2024
NETL
NSTL
万方数据