In:
Current Pharmaceutical Analysis, Bentham Science Publishers Ltd., Vol. 16, No. 7 ( 2020-08-17), p. 831-843
Abstract:
Kang Fu Xin liquid (KFX) is an official preparation made from
the ethanol extract product from P. Americana. The present quality control method cannot control the quality of the preparation well. The aim of the present study is to establish a convenient HPLC method
for multicomponents determination combined with fingerprint analysis for quality control of KFX. Methods: An HPLC-DAD method with gradient elution and detective wavelength switching program
was developed to establish HPLC fingerprints of KFX, and 38 batches of KFX were compared and evaluated by similarity analysis (SA), hierarchical clustering analysis (HCA), and principal component
analysis (PCA). Meanwhile, six nucleosides and three amino acids, including uracil, hypoxanthine, uric acid, adenosine, xanthine, inosine, tyrosine, phenylalanine and tryptophan in KFX were determined
based on the HPLC fingerprints. Results: An HPLC method assisted with gradient elution and wavelength switching program was established
and validated for multicomponents determination combined with fingerprint analysis of KFX. The results demonstrated that the similarity values of the KFX samples were more than 0.845. PCA
indicated that peaks 4 (hypoxanthine), 7 (xanthine), 9 (tyrosine), 11, 13 and 17 might be the characteristic contributed components. The nine constituents in KFX, uracil, hypoxanthine, uric acid, adenosine,
xanthine, inosine, tyrosine, phenylalanine and tryptophan, showed good regression (R2 〉 0.9997) within
test ranges and the recoveries of the method for all analytes were in the range from 96.74 to 104.24%. The limits of detections and quantifications for nine constituents in DAD were less than 0.22 and 0.43
μg•mL-1, respectively. Conclusion: The qualitative analysis of chemical fingerprints and the quantitative analysis of multiple
indicators provide a powerful and rational way to control the KFX quality for pharmaceutical companies.
Type of Medium:
Online Resource
ISSN:
1573-4129
DOI:
10.2174/1573412915666190328215231
Language:
English
Publisher:
Bentham Science Publishers Ltd.
Publication Date:
2020
SSG:
15,3
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