RESEARCH ARTICLE
Application of Design of Experiment and Design Space (DOE-DS) Methodology for the HPLC Separation of Panax Notoginseng Saponins
Shengyun Dai, Bing Xu*, Gan Luo, Jianyu Li, Zhong Xue, Xinyuan Shi, Yanjiang Qiao*
Article Information
Identifiers and Pagination:
Year: 2015Volume: 9
First Page: 47
Last Page: 52
Publisher ID: TOCENGJ-9-47
DOI: 10.2174/1874123101509010047
Article History:
Received Date: 08/01/2015Revision Received Date: 29/03/2015
Acceptance Date: 07/04/2015
Electronic publication date: 26/6/2015
Collection year: 2015
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Panax Notoginseng Saponins (PNS), extracted from the roots of the common TCM Panax notoginseng (Burk.) F.H.Chen, consist of notoginsenoside R1, ginsenoside Rg1, Re, Rb1, Rd and many other chemicals which haven’t been identified. Due to its popular pharmacological effects, it is of importance to control the quality. This study combines design of experiments and design space methodology to optimize the HPLC separation of PNS. Three common chromatographic parameters (i.e. the temperature, the initial proportion of acetonitrile and the gradient slope) were selected to construct a Box-Behnken design which consisted of 17 experiments. A quadratic model that was built from the experimental result was used to construct the design space. The optimal separation was predicted at temperature 20°C;, with a gradient starting at 15% of acetonitrile and a gradient slope of 0.55%/min. Accuracy profile approach was employed to validate the established HPLC method. The results clearly showed that quality by design methodology could be effectively applied to optimize the HPLC chromatographic conditions for the analysis of PNS.