Quantitative analysis of quercetin content of Blumea Balsamifera L. DC Dichloromethane leaf fraction using HPLC-RP-PDA and direct TLC-Bioautography

@#Quercetin, a flavonoid compound which is widely distributed in plants are considered ass beneficial physiologically due to attributed bioactivity such as anti-cancer, immunomodulatory, antidiabetic, and anti-inflammatory. In this study, the quercetin content from the dried Blumea balsamifera L. DC dried leaf was macerated with 95% ethanol and the concentrated extract was purified using Modified Kupchan method and flash chromatography. All fractions were tested for the presence of flavonoids using phytochemical screening and the selected dichloromethane fraction were further purified using another round of flash chromatograph. All resulting fractions and pooled samples were tested for the antioxidant property using the developed Thin Layer Chromatography (TLC)-Bioautography and separated compounds were derivatized with DPPH. Using the optimized TLC-Bioautography method, the quercetin content in the dichloromethane fraction was analyzed and compared with a reversed phase high performance liquid chromatography hyphenated with photodiode array detector (RP-HPLC-PDA). The calculated quercetin content from the pooled sample using TLC-bioautography method is 2.25 mg/ml and from RP-HPLC-PDA is 2.02 mg/ml which was not comparable statistically using unpaired t-test (p<0.05, α=0.05

Prediction of filamentous process performance attributes by CSL quality assessment using mid-infrared spectroscopy and chemometrics.

Every biopharmaceutical production process aims for control strategies to achieve process robustness in order to ensure consistent product quality. Process variability can origin from process parameters, the biological nature as well as from high lot-to-lot variability of raw materials. In filamentous processes raw materials with very complex matrices, such as corn steep liquor (CSL), are used, which are especially challenging to characterize. In this study, CSL was characterized in detail for its ingredients presenting an overall composition of its matrix of 50 analyzed components (19 amino acids, 5 organic acids, 8 reducing sugars, 7 water-soluble vitamins and 11 trace elements/minerals) in order to facilitate analytical reduction to fingerprinting methods FT-MIR was evaluated as fast and non-destructive spectroscopic fingerprinting method for adequate assessment of CSL quality. Feasibility of this method was shown by the correlation of certain bands in the spectra to substance groups present in CSL, such as the Amide I and II band and amino acids, respectively. Additionally, applicability of FT-MIR could be shown for classification of different CSL lots differing in provider and corn quality as well as for predictability of process performance attributes. The latter was demonstrated on a fed-batch filamentous fungi process for the production of antibiotics. By multivariate data analysis, it could be shown that CSL quality assessment via FT-MIR can be used for the prediction of maximal biomass generated in the process, with a correlation coefficient R2 of 0.964, as well as for the prediction of an unwanted impurity. The combination of a fast and easy method for CSL quality assessment and correlations of this quality with process performance attributes may facilitate the establishment of a risk-based acceptance criteria for raw material quality release of CSL. As CSL is a frequent used raw material, we believe that this method will also be useful for other processes and that CSL quality assessment is of high relevance in academia and industry.