Shao Jing-Yuan, Guo Jun-Lin, Guo Shang-Xin, Shu Zhi-Heng, Qu Hai-Bin, Gong Xing-Chu
Pharmaceutical Informatics Institute,College of Pharmaceutical Sciences,Zhejiang University Hangzhou 310058,China.
Graduate School,Tianjin University of Traditional Chinese Medicine Tianjin 300193,China.
Zhongguo Zhong Yao Za Zhi. 2019 Nov;44(22):4844-4851. doi: 10.19540/j.cnki.cjcmm.20190804.302.
In this work,a high performance liquid chromatography-ultraviolet( HPLC-UV) detection technology was used to establish fingerprint analysis method for Sanye Tangzhiqing Decoction following an analytical quality by design( AQb D) approach. Firstly,column temperature,flow rate,and gradient elution conditions were determined as the method parameters needing to be optimized. Then according to the results of definitive screening design,three critical method attributes( CMAs) were identified,including peak number,the percentage of common peak area to total peak area,and retention time of the last peak. A stepwise regression method was used then to build quantitative models between CMAs and method parameters. Probability-based design space was calculated and successfully verified using the experimental error simulation method. After the analysis conditions were optimized,the contents of six components,namely chlorogenic acid,paeoniflorin,rutin,hyperoside,quercetin-3-O-β-D-glucuronide,and salvianolic acid B were simultaneously determined. There were 19 common peaks in the fingerprint and their common peak area accounted for 96% of the total peak area. Both fingerprint and quantitative analysis methods were validated applicable in methodology study,and they can be applied to determine new samples.
在本研究中,采用高效液相色谱 - 紫外(HPLC - UV)检测技术,按照质量源于设计(AQbD)方法建立了三叶青止清方的指纹图谱分析方法。首先,确定柱温、流速和梯度洗脱条件为需要优化的方法参数。然后根据确定性筛选设计结果,确定了三个关键方法属性(CMA),包括峰数、共有峰面积占总峰面积的百分比以及最后一个峰的保留时间。随后采用逐步回归方法建立CMA与方法参数之间的定量模型。计算了基于概率的设计空间,并使用实验误差模拟方法成功验证。优化分析条件后,同时测定了绿原酸、芍药苷、芦丁、金丝桃苷、槲皮素 - 3 - O - β - D - 葡萄糖醛酸苷和丹酚酸B六种成分的含量。指纹图谱中有19个共有峰,其共有峰面积占总峰面积的96%。指纹图谱和定量分析方法在方法学研究中均验证适用,可用于新样品的测定。