Establishment of the Quantitative Analysis of Multiindex in Euphorbia lathyris by the Single Marker Method for Euphorbia lathyris Based on the Quality by Design Concept

A brief review on application of design of experiment for the analysis of pharmaceuticals using HPLC

The quality pioneer Dr. Joseph M. Juran first proposed the idea of quality by design. According to him, pharmaceutical quality by design is an organised approach to product development that starts with predetermined goals and places an emphasis on product, process understanding, control based on reliable science and quality risk management. The quality of a product or process can typically be affected by a number of input elements. Design of experiments has been employed widely recently to understand the impacts of multidimensional and interactions of input parameters on the output responses of analytical procedures and pharmaceutical goods. Depending on the design of experiments objectives, screening, characterization, or optimization of the process and formulation, a variety of designs, such as factorial or mixture, can be used. The most popular designs used in the stage of screening or factor selection are the 2-Level Factorial and Plackett-Burman designs, both of which have two levels for each factor (k), both economical and effective, and in optimization widely used designs in this step are full factorial at three levels, central composite, Box-Behnken design. The analysis of variance, regression significance, and lack of fit of the regression model were some of the key topics covered in the discussion of the main components of multiple regression model adjustment. Design of experiments is thus the primary element of the formulation and analytical quality by design. The details about design of experiments used for the analysis of pharmaceutical formulation using HPLC.

Explore the Lipid-Lowering and Weight-Reducing Mechanism of Lotus Leaf Based on Network Pharmacology and Molecular Docking

Objective

To predict the target of the active ingredient of lotus leaf for lowering fat and losing weight. Explore its multicomponent, multitarget, multipath mechanism.

Methods

Screen the main active ingredients of lotus leaves through the TCMSP database, and use the TCMSP database to predict the potential targets of the active ingredients. Obtain obesity-related targets from the human genome annotation (GeneCards) database. Use Venn software to take the intersection of the two to obtain the effect target of the lotus leaf lipid-lowering and weight-reducing effects. Use Cytoscape 3.6.0 software to construct an effective ingredient-target network. Use the STRING database to construct an intersection target protein interaction (PPI) network, visualize it with Cytoscape 3.6.0 software, and perform network topology analysis to obtain the core target. Use the DAVID database to perform gene ontology (GO) and metabolic pathway (KEGG) enrichment analysis for the above targets. Use AutoDockTools software for molecular docking to verify the binding strength.

Results

A total of 15 main active ingredients such as quercetin, isorhamnetin, sitosterol, and kaempferol were obtained, which can act on 135 targets related to obesity. These targets are significantly enriched in multiple GO and KEGG entries such as hypoxia response, positive regulation of gene expression, response to toxic substances, aging, and positive regulation of RNA polymerase II promoter transcription. Molecular docking shows that flavonoids such as quercetin have better binding to the target protein Akt1.

Conclusion

The lipid-lowering and weight-reducing effects of lotus leaf embody the characteristics of multicomponent, multitarget, and multipathway of traditional Chinese medicine, which provides a certain scientific basis for the screening and in-depth study of the effective ingredients of lotus leaf.