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引用本文:李卓伦,周霖,王肖辉,孙志,左莉华,周珮珮,王旺,曹辉,冯娟娟,章贤,朱君君,张晓坚.基于UPLC指纹图谱结合化学模式识别的芪参益气滴丸质量控制研究[J].中国现代应用药学,2019,36(14):1754-1760.
LI Zhuolun,ZHOU Lin,WANG Xiaohui,SUN Zhi,ZUO Lihua,ZHOU Peipei,WANG Wang,CAO Hui,FENG Juanjuan,ZHANG Xian,Zhu Junjun,ZHANG Xiaojian.Quality Control Research of Qishen Yiqi Dripping Pills Based on UPLC Fingerprint Combined with Chemical Pattern Recognition[J].Chin J Mod Appl Pharm(中国现代应用药学),2019,36(14):1754-1760.
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基于UPLC指纹图谱结合化学模式识别的芪参益气滴丸质量控制研究
李卓伦1,2, 周霖1,2, 王肖辉3, 孙志1,2, 左莉华1,2, 周珮珮1,2, 王旺4, 曹辉5, 冯娟娟6, 章贤1,2, 朱君君7, 张晓坚1,2
1.郑州大学第一附属医院, 药学部, 郑州 450052;2.河南省精准临床药学重点实验室, 郑州 450052;3.郑州大学第一附属医院, 超声科, 郑州 450052;4.郑州大学生理学与神经生物学系, 郑州 450001;5.郑州大学第一附属医院, 腔内血管外科, 郑州 450052;6.郑州大学第一附属医院, 康复医学科, 郑州 450052;7.河南理工大学医学院, 河南 焦作 454000
摘要:
目的 采用超高效液相色谱法建立芪参益气滴丸的指纹图谱,并结合化学模式识别技术对其进行系统、全面和科学的质量评价。方法 采用Waters超高效液相色谱仪,ACQUITY UPLC®HSS T3色谱柱,以乙腈-0.1%甲酸水为流动相进行梯度洗脱,检测波长为256 nm,建立10批次芪参益气滴丸的指纹图谱。通过相似度分析并结合聚类分析(cluster analysis,CA)、主成分分析(principal component analysis,PCA)及正交偏最小二乘法-判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)模式识别技术对芪参益气滴丸的总体质量进行分析评价。结果 建立的指纹图谱共标定53个共有峰,经对照品进行化学指认并鉴定了其中的14个色谱峰。10批供试品的相似度均>0.94,表明该药物总体质量较为稳定;但通过CA及PCA均发现不同批次药物质量之间仍然存在有微小差异,且主要分为2大类,最后进一步采用OPLS-DA筛选出了导致批次药物质量差异的3个共有峰。结论 本研究建立的分析方法科学、准确、可靠且简便易行,指纹图谱结合化学模式识别技术可更加系统、全面地评价芪参益气滴丸的药物质量,同时为今后中药及其制剂更进一步的质量控制研究奠定了坚实的理论基础。
关键词:  芪参益气滴丸  指纹图谱  化学模式识别  质量控制
DOI:10.13748/j.cnki.issn1007-7693.2019.14.006
分类号:R284.1;R917.101
基金项目:常州四药临床药学科研基金(CZSYJJ16030);河南省科技攻关项目(182102310243);河南省高等学校重点科研项目(19A320070)
Quality Control Research of Qishen Yiqi Dripping Pills Based on UPLC Fingerprint Combined with Chemical Pattern Recognition
LI Zhuolun1,2, ZHOU Lin1,2, WANG Xiaohui3, SUN Zhi1,2, ZUO Lihua1,2, ZHOU Peipei1,2, WANG Wang4, CAO Hui5, FENG Juanjuan6, ZHANG Xian1,2, Zhu Junjun7, ZHANG Xiaojian1,2
1.The First Affiliated Hospital of Zhengzhou University, Department of Pharmacy, Zhengzhou 450052, China;2.Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou 450052, China;3.The First Affiliated Hospital of Zhengzhou University, Ultrasonic Department, Zhengzhou 450052, China;4.Department of Physiology and Neurobiology, Zhengzhou University, Zhengzhou 450001, China;5.The First Affiliated Hospital of Zhengzhou University, Department of Physiology and Neurobiology, Zhengzhou 450052, China;6.The First Affiliated Hospital of Zhengzhou University, Department of rehabilitation medicine, Zhengzhou 450052, China;7.Medical college, Henan Polytechnic University, Jiaozuo 454000, China
Abstract:
OBJECTIVE To establish the UPLC fingerprint of Qishen Yiqi Dripping pills and conduct a systemic, comprehensive quality evaluation of the drug using a chemical pattern recognition method. METHODS Ultra-high performance liquid chromatography instrument and ACQUITY UPLC® HSS T3 chromatographic column was employed, the separation was performed with the mobile phase consisting of acetonitrile and 0.1% formic acid aqueous solution, and the detection wavelength was set at 256 nm to establish the UPLC fingerprint of Qishen Yiqi Dripping pills. Then, the further quality assessment of the drug was carried out by similarity evaluation, cluster analysis(CA), principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA). RESULTS Fifty-three peaks were recognised as common peaks in the fingerprint, 14 peaks were identified using standard references. The similarity value of the drugs were all >0.94, indicating a relatively stable quality of the quality. Little difference was then discovered between the batches of the drug by CA and PCA. Finally, 3 peaks were recognised as the quality makers using a OPLS-DA method. CONCLUSION The analysis method established in this study is scientific, accurate, reliable and simple; the drug quality of Qishen Yiqi Dripping pills can be evaluated systematically and comprehensively using a fingerprint combined with chemical pattern recognition technique; what's more, it will also lay a solid theoretical basis for the further quality control of traditional Chinese medicine and its preparations at the same time.
Key words:  Qishen Yiqi Dripping pills  fingerprint  chemical pattern recognition  quality control
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