Quantitative Evaluation of the Quality of Shiqi Waigan Granules Based on Fingerprinting and Multi‐Indicator Components With Multivariate Statistical Analysis

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.