质量分析

基于指纹图谱与多指标成分定量结合化学模式识别分析的小儿热速清颗粒质量评价研究

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  • 1.江西中医药大学 现代中药制剂教育部重点实验室,南昌 330004;
    2.江西倍肯药业有限公司,宜春 336400
第一作者 Tel:18720406827;E-mail:1479063375@qq.com
* Tel:(0791)87118658;E-mail:paln7@163.com

修回日期: 2024-04-15

  网络出版日期: 2024-08-07

Quality evaluation of Xiaoer Resuqing granules based on fingerprint and quantitative analysis of multi-index components combined with chemical pattern recognition analysis

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  • 1. Key Laboratory of Modern Preparation of Traditional Chinese Medicine, Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang 330004, China;
    2. Jiangxi Beken Pharmaceutical Co., Ltd., Yichun 336400, China

Revised date: 2024-04-15

  Online published: 2024-08-07

摘要

目的: 采用指纹图谱、多指标成分含量测定与化学模式识别分析技术相结合的方法研究不同批次小儿热速清颗粒,为其质量评价提供依据。方法: 采用SuperLu C18色谱柱(250 mm×4.6 mm,5 μm),流动相为甲醇(A)-0.1%磷酸水(B),梯度洗脱,体积流量1.0 mL·min-1,柱温30 ℃,检测波长280 nm,对15批小儿热速清颗粒指纹图谱进行相似度评价,指认出11个特征成分,并对葛根素、连翘酯苷A、连翘苷、黄芩苷、汉黄芩苷、黄芩素、汉黄芩素7个有效成分进行含量测定,采用聚类分析(HCA)及主成分分析(PCA)对15批样品进行分类并进行正交最小偏二乘法-判别分析(OPLS-DA),筛选出样品批次间差异成分。结果: 建立了小儿热速清颗粒HPLC指纹图谱及7个成分的含量测定方法,且这2种方法学验证的结果均符合要求,确定了28个共有峰,并指认了11个色谱峰,15个批次相似度范围为0.995~0.999;HCA和PCA结果显示15个批次成分聚为2类,OPLS-DA分析筛选出13个造成样品批次间差异的标志物;多指标成分含量测定表明不同批次间小儿热速清颗粒中化学成分含量差异性较小。结论: 建立的小儿热速清颗粒HPLC指纹图谱及7个成分含量测定方法的专属性强,准确、可靠,结合化学模式识别可有效的用于小儿热速清颗粒的质量控制。

本文引用格式

周爱鲜, 廖正根, 勒孚仕, 刘慧星, 赵国巍, 梁新丽 . 基于指纹图谱与多指标成分定量结合化学模式识别分析的小儿热速清颗粒质量评价研究[J]. 药物分析杂志, 2024 , 44(6) : 1062 -1073 . DOI: 10.16155/j.0254-1793.2024.06.18

Abstract

Objective: To study different batches of Xiaoer Resuqing granules by combining the method of fingerprint, multi-index component content determination and chemical pattern recognition analysis technology, and to provide the basis for its quality evaluation. Methods: The chromatographic SuperLu C18(250 mm×4.6 mm, 5 μm) column was adopted with mobile phase composed of methanol (A)-0.1% phosphoric acid (B) with gradient elution at a flow rate of 1.0 mL·min-1.The column temperature was 30 ℃, and the detection wavelength was 280 nm. Eleven characteristic components were identified, and the contents of seven active components, including puerarin, forsythiaside A, phillyrin, baicalin, wogonoside, baicalein and wogonin were determined. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to classify 15 batches of samples, and orthogonal least partial squares discriminant analysis (OPLS-DA) was performed. To screen out the difference components between batches of Xiaoer Resuqing granules. Results: The HPLC fingerprint of Xiaoer Resuqing granules and the content determination method of 7 components were established, the results of the two methods met the requirements. Twenty-eight common peaks were identified, 11 chromatographic peaks were identified, and the similarities of 15 batches of samples ranged from 0.995 to 0.999. HCA and PCA results showed that 15 batches were clustered into two categories, and OPLS-DA screened out 13 markers that caused the differences among the 15 batches of samples. There was little difference in the contents of ingredients. Conclusion: The established HPLC fingerprint of Xiaoer Resuqing granules and the determination method of 7 components are specific, accurate and reliable. Combined with chemical pattern recognition, it can be effectively used for the quality control of Xiaoer Resuqing granules.

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