Lin Feng, Yaling An, Fang Mei, Tiyu Xia, Huiling Jiang, Lihua Peng, Weilin Qiao, De-An Guo
College of Pharmacy, Changchun University of Traditional Chinese Medicine, Changchun, Jilin, China.
Zhongshan Institute for Drug Discovery, Zhongshan, Guangdong, China.
Biomed Chromatogr. 2025 Nov;39(11):e70221. doi: 10.1002/bmc.70221.
Shiqi Waigan Granules (SWG) are a widely used traditional Chinese medicine for treating common colds, yet a rapid and holistic quality-control protocol has been lacking. In this work, an HPLC fingerprint was built on an Agilent ZORBAX SB-C18 column (4.6 × 250 mm, 5 µm) with acetonitrile-0.1% phosphoric acid gradient elution, 330 nm detection, 40°C column temperature, and 0.6 mL/min flow. Eleven commercial batches were profiled, yielding nine consistent common peaks (similarity > 0.9). Eight of these peaks were unequivocally identified and quantified, all showing excellent linearity (r > 0.9999). Orthogonal partial least-squares discriminant analysis (OPLS-DA) with SIMCA software and variable-importance-in-projection (VIP) scoring highlighted four compounds whose levels differ most among batches and therefore drive product quality. Integrating fingerprinting, quantification, and multivariate statistics thus furnishes a reliable, efficient strategy for routine quality control of Shiqi Waigan Granules.
十芪外感颗粒（SWG）是一种广泛用于治疗感冒的中药，但一直缺乏快速、全面的质量控制方案。在本研究中，采用安捷伦ZORBAX SB-C18柱（4.6×250 mm，5 µm）建立高效液相色谱指纹图谱，以乙腈-0.1%磷酸梯度洗脱，检测波长330 nm，柱温40°C，流速0.6 mL/min。对11个商业批次进行了分析，得到9个一致的共有峰（相似度>0.9）。其中8个峰得到明确鉴定和定量，均显示出良好的线性关系（r>0.9999）。使用SIMCA软件进行的正交偏最小二乘判别分析（OPLS-DA）和投影变量重要性（VIP）评分突出了4种化合物，其含量在不同批次间差异最大，因此对产品质量起关键作用。将指纹图谱、定量分析和多元统计相结合，为十芪外感颗粒的常规质量控制提供了一种可靠、有效的策略。
