Statistical Model Based HPLC Analytical Method Adjustment Strategy to Adapt to Different Sets of Analytes in Complicated Samples

Phytochemical Analysis : PCA
Binjun YanFanzhu Li

Abstract

On account of the complicated compositions of the products like traditional Chinese medicines (TCMs) and functional foods, it is a common practice to determine different sets of analytes in the same product for different purposes. To efficiently develop the corresponding HPLC methods, a statistical model based analytical method adjustment (SMB-AMA) strategy was proposed. In this strategy, the HPLC data acquired with design of experiments methodology were efficiently utilised to build the retention models for all the analytes and interferences shown in the chromatograms with multivariate statistical modelling methods. According to the set of analytes under research, Monte-Carlo simulations were conducted based on these retention models to estimate the probability of achieving adequate separations between all the analytes and their interferences. Then the analytical parameters were mathematically optimised to the point giving a high value of this probability to compose a robust HPLC method. Radix Angelica Sinensis (RAS) and its TCM formula with Folium Epimedii (FE) were taken as the complicated samples for case studies. The retention models for the compounds in RAS and FE were built independently with correlation coefficients all...Continue Reading

References

Jul 16, 2013·Journal of Pharmaceutical and Biomedical Analysis·Benjamin DebrusSerge Rudaz
Jan 19, 2015·Journal of Chromatography. a·Eva TytecaGert Desmet

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