Characteristic Chromatogram and Index Component Contents of Substance Benchmark of Classic Formula Qingwei Power
OBJECTIVE To establish an HPLC characteristic spectrum and content determination method for the reference mate-rial of the classic formula Qingwei Powder,and control its quality to ensure subsequent preparation.METHODS Following ancient books and combining with the investigation of the previous preparation process,15 batches of Qingwei Powder material standards were prepared.HPLC was used to establish the material standard feature map,and the similarity was calculated using the Chinese medicine chromatographic fingerprint similarity evaluation system(2012 version);seven indicator components from five medicinal herbs were used as the reference content determination indicators for Qingwei Powder,and an HPLC content determination method was established for 15 batches of samples.RESULTS The similarity of the characteristic spectra was≥0.975;13 common peaks were calibrated;and 7 common peaks were identified for chemical composition,including catalpol(peak 1),ferulic acid(peak 5),isoferulic acid(peak 6),berberine hydrochloride(peak 7),palmatine hydrochloride(peak 8),paeonol(peak 12),and ligustilide(peak 13).Two sets of indicator component content determination methods have been established.Firstly,the contents of catalpol,ferulic acid,isoferulic acid,and paeonol were determined,and the four component contents were specified to be 1.48-2.76、0.14-0.26、0.48-0.90、1.72-3.19 mg·g-1,respectively;secondly,the contents of coptisine hydrochloride,palmatine hydrochloride,and ber-berine hydrochloride was determined,and it was specified that the content of the three components should be 0.65-1.21、0.57-1.07、1.86-3.45 mg·g-1,respectively.CONCLUSION A quality control method for the reference material of Qingwei Powder has been established through the characteristic spectrum and content determination method.This method is simple and reliable,providing a basis and foundation for subsequent quality control and formulation development.
万方数据
维普
