RÉSUMÉ
Objective:To optimize the decoction process of Digda-4 decoction(DGD-4D), and provide reference for the standardization study of decoction of Mongolian medicine decoction. Method:Taking DGD-4D as model drug, different decoction methods of Mongolian medicine were compared, HPLC was used to determine contents of aesculetin, geniposide, picroside Ⅰ and picroside Ⅱ.On the basis of single factor tests, central composite design-response surface methodology was adopted to optimize the decoction process of DGD-4D with transfer rates of 4 components and dry extract rate as indexes, regression model fitting was carried out by Design-Expert 8.0.6 software, prediction model of process parameters was established, and the optimal process was verified. Result:The optimal decoction condition of DGD-4D was determined to be adding 40 times the amount of water and decocting for 17 min, decocting once.Transfer rates of aesculetin, geniposide, picroside Ⅰ, picroside Ⅱ and dry extract rate were 70.01%, 94.11%, 61.23%, 92.32%, 32.89%, respectively. Conclusion:The optimum decoction process of DGD-4D is established, it has important reference significance for excavating, sorting, improving the level of Mongolian medicine preparations and ensuring the consistency of their clinical efficacy.
RÉSUMÉ
To establish and validate the design space of the Digeda-4 flavored decoction( DGD-4D) extraction process by using the quality by design( Qb D) concept. With DGD-4D decoction pieces as a model drug,with the transfer rate of aesculin,picroside I,picroside Ⅱ,geniposide and the yield of extract as critical quality attributes( CQAs),the single factor experiment design was used to determine the level of each factor; the Plackett-Burman experiment design was used to select the critical process parameters( CPPs);and the Box-Behnken experiment design was used to optimize the extraction process. The design space of the DGD-4D extraction process was established,and finally,four experimental points were selected to verify the established model. The single factor experiment determined the levels of each factor,including soaking time 60 min and 30 min,water adding volume 12 times and 8 times,extraction time 90 min and 30 min,number of extraction times 3 times and 1 time,as well as extraction temperature 100 ℃ and 90 ℃.By Plackett-Burman experimental design,the DGD-4D water addition,extraction time and number of extraction times were determined to be CPPs. The Box-Behnken experimental variance analysis showed that P of the regression model was less than 0. 01 and the misstated value was more than 0. 01,indicating that the model had good predictive ability,and the operation space of CPPs in the DGD-4D extraction process was determined as follows: the amount of water addition was 10-12 times; extraction time 50-80 min; and number of extraction times was 3 times. The design space of DGD-4D extraction process based on the concept of Qb D is conducive to improving the stability of product quality and laying a foundation for the future development of DGD-4D.
Sujet(s)
Chimie pharmaceutique , Méthodes , Médicaments issus de plantes chinoises , Chimie , Plan de rechercheRÉSUMÉ
To establish the high performance liquid chromatography (HPLC) fingerprint for Digeda-4 decoction (DGD-4D), determine the contents of aesculetin, geniposide, picroside Ⅰ, picroside Ⅱ and ellagicacid in DGD-4D, and provide the scientific foundation for quality control of DGD-4D. The analysis was performed on Diamonsil(2) C₁₈ (4.6 mm×250 mm,5 μm) column, with methanol-0.1% phosphoric acid aqueous solution as mobile phase for gradient elution. The flow rate was 1.0 mL·min⁻¹; injection size was 10 μL; temperature was maintained at 30 °C, and the detection wavelength was set at 254 nm. The common mode of DGD-4D HPLC fingerprint was established, and the hidden information was analyzed by Chemometrics. Chromatographic peaks for DGD-4D were identified by HPLC and quantitative analysis was conducted for characteristic peaks. There were 17 common peaks in the fingerprints and the similarity of the fingerprints was over 0.9 in all 15 batches. The samples were broadly divided into four kinds by principal component analysis and clustering analysis. Four marker compounds were verified by partial least squares discriminant analysis, and No. 9, 12 and 14 peaks were identified as geniposide, picroside Ⅱ, and picroside Ⅰ respectively. The average recoveries were in the range of 95.91%-97.31%. The HPLC fingerprint method for content determination is reliable, accurate, rapid, simple, and reproducible, and can be used as one of the effective methods to control the quality of DGD-4D.