Quality Evaluation of Qingwei Huanglian Pills Based on Fingerprint and Quantitative Analysis of Multi-Index Components Combined with Chemical Pattern Recognition Analysis.

Abstract

Qingwei Huanglian Pills (QHPs) is one of the most commonly used traditional Chinese medicine preparations for the treatment of mouth and tongue sores, but the existing quality evaluation standards have certain shortcomings and deficiencies. An effective and scientific quality evaluation method plays a vital role in medication safety. In this study, fingerprint and quantitative analysis of multi-index components combined with chemical pattern recognition analysis was used to comprehensively evaluate the quality of QHPs. The fingerprints of 15 batches of QHPs were generated and evaluated for similarity, with 10 characteristic peaks identified. Clustering hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to cluster and rank the 15 batches, while simultaneously identifying the components responsible for differences between batches. The HPLC fingerprints of QHPs, along with the content determination of 10 components, were established. Twenty-eight common peaks were identified, and 10 components were specified. The similarity between the 15 batches of samples ranged from 0.983 to 0.999. Cluster analysis and comprehensive score ranking of 15 batches of samples were performed by HCA and PCA, respectively, and 13 chemical markers affecting batch differences were screened by OPLS-DA. The method established here can serve as a reference for the quality evaluation and product quality control of QHPs.