Chemometric Approach to Assess Response Correlation and its Classification in simplex centroid design for Pre-Optimization stage of Catechin-SNEDDS

Abstract

Catechins are isolated from tea leaves and shown to have pharmacological activities. However, the permeability and absorption capacity of the digestive tract is low, thus affecting the value of bioavailability. Self-nano emulsifying drug delivery system (SNEDDS) is formulated as a breakthrough in nano delivery to increase the value of bioavailability and stability in a model of natural compounds, namely catechins. This study applies chemometrics to the simplex centroid design (SCD) to analyze the catechin-SNEDDS pre-optimization design. The factors defined include oleic acid, croduret 50-SS, and propylene glycol. Evaluation parameters include emulsification time, percent transmittance (%T), freeze-thaw, and endurance test. The results showed a formula that met the requirements at the time of emulsification, stability, and %T. There were four clusters of results from the principal component analysis - cluster analysis (PCA-CA) in the SCD formula. The evaluation between responses in the SCD optimization design is indicated to have a positive correlation. Analysis using multivariate chemometric can describe the characteristics of each formula and the response based on the parameters used, which refers to the similarity, grouping, and correlation of each formula and response. The PCA-CA technique can group formulas from SCD in similar clusters and provide important information regarding response patterns or correlations.

Evaluation of Response Corellation Using Chemometrics Analysis for Pre-Optimization Quercetin – Self Emulsion Formulation

“…Plot visualizations useful in interpreting data from PCA results include score plots, loading plots, and biplots. The correlation between the responses of the parameters specified in the SCD was well described using a loading plot (Shiyan, Zubaidah, et al, 2021). Score plot can also be supported by cluster analysis in a dendrogram (Triyasmono et al, 2021;Widyastuti et al, 2021).…”

“…The cycle in this test was repeated six times. Observation of the stability of quercetin-SEFs by visually observing the parameters of clarity, phase separation, and precipitate (Shiyan, Zubaidah, et al, 2021).…”

“…Quercetin-SEFs were stored at 25-30°C for 24 hours. Quercetin-SEFs was dissolved into aquadest up to 5 mL and mixed by inverting the vial until the SEFs dissolved in aquadest and become quercetin emulsion (Halder et al, 2021;Shiyan, Zubaidah, et al, 2021).…”

Screening of Antibacterial Compounds Against Escherichia coli from Hanjeli Seeds (Coix lacryma-jobi) Based on Metabolomics

“…19 The chemometric pattern recognition technique used in this study is principal component analysis (PCA) because it can facilitate visualization in grouping data, evaluating similarities between groups or classes, and finding factors or reasons behind observed patterns through correlations based on the chemical or physicochemical properties of the samples. 20 In this study, the antibacterial compounds in hanjeli seed extract were predicted using LC-MS/MS-based metabolomic. LC-MS/MS results were further analyzed by PCA to determine the grouping pattern between the selected extracts with and without the addition of E. coli bacteria.…”