Quality consistency evaluation of Kudiezi Injection based on multivariate statistical analysis of the multidimensional chromatographic fingerprint.

Traditional Chinese Medicine Injection (TCMI) was restricted due to the batch-to-batch variability caused by the variable compositions of botanical raw materials and complexities of the current manufacturing process. To evaluate and control the quality of Kudiezi Injection (KDZI), a comprehensive and practical method based on multidimensional chromatographic fingerprint associated with multivariate statistical analysis was proposed. The multidimensional chromatographic fingerprint was established by integrating three kinds of chromatographic fingerprints, including High Performance Liquid Chromatography-Ultraviolet spectrum (HPLC-UV), Gas Chromatography-Mass Spectrometer (GC-MS) and High performance ion-exchange chromatography (HPIEC), which were used to detect flavones, nucleosides, organic acids, amino acids and saccharides in KDZI. In addition, four main multivariate statistical analyses were compared to assess the batch-to-batch consistency of samples. Results showed that the cosine method, which has been widely used in the quality evaluation of TCM, failed to distinguish the differences among batches based on neither chromatographic peaks' area nor contents information. t-test and Bayes' theorem could reveal the content difference among batches, while hierarchical clustering analysis could differentiate KDZI batches, and Luteolin-7-O-β-D-glucuronopyranoside, Tau, Ser, guanine and allose were the main indicators. In conclusion, multidimensional chromatographic fingerprints could reflect the quality information of KDZI comprehensively and hierarchical clustering analysis was suitable to identify the differences among batches. This could provide an integrated method for consistency evaluation of TCMI, process improvement of TCMI and solving similar problems in TCMI.