A Preferable Approach for the Quality Control of Xiaoer Chiqiao Qingre Granules Based on the Combination of Chromatographic Fingerprints and Chemometrics

Tong Xu; Xiaoqi Li; Mengmeng Huang; Qi Wang; Chao Li; Gang Tian; Yan Chen

doi:10.1155/2020/6836981

A Preferable Approach for the Quality Control of Xiaoer Chiqiao Qingre Granules Based on the Combination of Chromatographic Fingerprints and Chemometrics

J Anal Methods Chem. 2020 Sep 29:2020:6836981. doi: 10.1155/2020/6836981. eCollection 2020.

Authors

Tong Xu^{1

2}, Xiaoqi Li^{1

3}, Mengmeng Huang^{1

3}, Qi Wang^{1

3}, Chao Li⁴, Gang Tian⁴, Yan Chen^{1

3}

Affiliations

¹ Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210028, China.
² The State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
³ Multi-Component of Traditional Chinese Medicine and Microecology Research Center, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing 210028, China.
⁴ Jumpcan Pharmaceutical Co., Ltd., Taixing 225400, China.

Abstract

A preferable approach of a combination of a multiwavelength fusion HPLC fingerprint and chemometrics for the quality control of Xiaoer Chiqiao Qingre granules (XCQG) was established in this study. A single-wavelength HPLC fingerprint was performed to identify 18 peaks as common peaks in the beginning, and 12 of them were recognized by HPLC-Q/TOF-MS. To overcome the limitation of the single-wavelength HPLC fingerprint, a three-wavelength (230 nm, 250 nm, and 330 nm) fusion fingerprint was established for a more thorough quality assessment. Six main active ingredients (geniposide, paeoniflorin, forsythin, forsythoside A, baicalin, and wogonoside) were selected as chemical markers for simultaneous quantitative analysis, while the results indicated that the content of other five ingredients except forsythoside A presented comparatively stable. Chemometrics including hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the homogeneity and heterogeneity of sixteen batches of XCQG. The results of the multiwavelength fingerprint were clearly classified into two clusters by HCA, whereas the single-wavelength fingerprint showed no distinct difference between them. OPLS-DA was further employed to prove that the above six main active ingredients made great contributions to clustering. In summary, this integrated analysis provided a better promoted and more comprehensive method to control the quality of XCQG.