[Study on rapid quality analysis method of Shengxuebao Mixture].

A rapid analysis method based on ultraviolet-visual(UV-Vis) spectroscopy, near infrared(NIR) spectroscopy and multivariable data analysis was established for quality evaluation of Shengxuebao Mixture. The contents of eight active ingredients of Shengxuebao Mixture including albiflorin, paeoniflorin, 2, 3, 5, 4'-tetra-hydroxy-stilbene-2-O-ß-D-glucopyranoside, specnuezhenide,ecliptasaponin D, emodin, calycosin-7-glucoside and astragaloside Ⅳ were simultaneously detected by using this method. HPLC-UV-MS was used as a reference method for determining the contents of these ingredients. Partial least squares(PLS) analysis was implemented as a linear method for multivariate models calibrated between UV spectrum/NIR spectrum and contents of 8 ingredients. Finally, the performance of the model was evaluated by 24 batches of test samples. The results showed that both UV-Vis and NIR models gave a good calibration ability with an R~2 value above 0.9, and the prediction ability was also satisfactory, with an R~2 value higher than 0.83 for UV-Vis model and higher than 0.79 for NIR model. The overall results demonstrate that the established method is accurate, robust and fast, therefore, it can be used for rapid quality evaluation of Shengxuebao Mixture.

[Quantitative analysis method of Shengxuebao Mixture by HPLC-UV-MS based on quality by design concept].

In this study, the HPLC-UV-MS method for the simultaneous determination of eight active ingredients of Shengxuebao Mixture were developed based on the concept of quality by design（QbD）with a stepwise optimization approach. After the analytical target profile（ATP）had been defined, albiflorin, paeoniflorin, 2, 3, 5, 4'-tetra-hydroxy-stilbene-2-O-ß-D-glucopyranoside, specnuezhenide, ecliptasaponin D, emodin, calycosin-7-glucoside, and astragaloside Ⅳ were identified as the indicator components. The resolution and the signal-to-noise ratio of indicator components were then selected as critical method attributes (CMA) for the first step optimization. According to the results collected from fractional factorial design, critical method parameters (CMP) were determined with a multiple linear regression method, which included the amount of acid addition in the mobile phase, temperature, gradient, and wavelength. After that, the amount of acid addition and the wavelength were optimized to improve the resolution and the signal-to-noise ratio of the indicator components. The peak symmetry factors of specnuezhenide and emodin were then set as CMA for the second step optimization. The Box-Behnken designed experiments were conducted. The temperature and gradient were optimized after modelling. The design space were calculated and verified. The optimized analytical method was validated, and the results showed a good precision, accuracy and stability, which means that it can be used for the quantification of the indicator components in Shengxuebao Mixture.