Issue 23, 2017

Integrating qualitative and quantitative assessments of Yougui pill, an effective traditional Chinese medicine, by HPLC-LTQ-Orbitrap-MSn and UPLC-QqQ-MS/MS

Abstract

Yougui pill (YGP) is a well-known Chinese medicine formula with definite clinical effects on kidney-yang deficiencies such as infertility. However, Aconitum carmichaeli var. carmichaeli, one of the herbs contained in YGP, shows several side effects. Therefore, it is important to carry out strict and systematic quality evaluation on YGP to ensure its effects and safety. In the present study, qualitative and quantitative analyses were performed on YGP. First, an HPLC-LTQ-Orbitrap-MSn method was applied to validate the chemical profile of YGP. Eighty-three compounds were identified, including iridoids, flavones and alkaloids. Second, an UPLC-QqQ-MS/MS method was used for the simultaneous quantitation of 16 targeted compounds in YGP. The method showed a good linear correlation (R > 0.995) over a wide range and a high sensitivity, as established by LOD (0.04–0.40 ng mL−1) and LOQ (0.10–1.00 ng mL−1). The RSD values of intra- and inter-day precisions were less than 10%. The RSD values of repeatability and stability were less than 5%, and recovery assays were between 85.8% and 96.2%. The cluster analysis indicated that the qualities of YGP from two manufacturers were very different. The present integrated qualitative and quantitative assessment of YGP provides a good example of quality evaluation strategy to assess Chinese medicine formulas.

Graphical abstract: Integrating qualitative and quantitative assessments of Yougui pill, an effective traditional Chinese medicine, by HPLC-LTQ-Orbitrap-MSn and UPLC-QqQ-MS/MS

Supplementary files

Article information

Article type
Paper
Submitted
27 Jan 2017
Accepted
16 May 2017
First published
16 May 2017

Anal. Methods, 2017,9, 3485-3496

Integrating qualitative and quantitative assessments of Yougui pill, an effective traditional Chinese medicine, by HPLC-LTQ-Orbitrap-MSn and UPLC-QqQ-MS/MS

H. Liu, F. Qiu, B. Bian, X. Yang, H. Zou, H. Zhao, Z. Chen, Q. Wang, H. Zhao and L. Wang, Anal. Methods, 2017, 9, 3485 DOI: 10.1039/C7AY00259A

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