Dataset Information

Factorial design-assisted spectroscopic determination of oxybutynin hydrochloride.

ABSTRACT: In this study, we have developed two facile spectroscopic methods for quantifying oxybutynin (OBT) hydrochloride in its pure form and tablets using design of experiments (DOEs). The spectroscopic methods depended on the ion-pair complex formation between the tertiary amino group in the drug and eosin in 0.2 M acetate buffer of pH 4. Method I involves spectrophotometric measurement of the absorbance of the developed complex at 550 nm and showed linearity through 1.0-10.0 µg ml^-1. Method II involves spectrofluorometric measurement of the quenching influence of OBT on the native fluorescence of eosin (λ excitation/λ emission of 304/548 nm) and showed linearity through 1.0-6.0 µg ml^-1. Critical parameters were identified through preliminary trials and optimized using the DOE. Additionally, the quenching mechanism was investigated and the pathway of the reaction was postulated. The fluorescence quenching constant and thermodynamic parameters were explored using the Stern-Volmer plot and Van't Hoff graph, respectively. Assessments conducted via analytical ecoscale revealed the 'excellent-greenness' of the methodology. The two methods have the potentials of being green and fast compared with other reported methods.

SUBMITTER: Yosrey E

PROVIDER: S-EPMC8611342 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundPretreatments are one of the main bottlenecks for the lignocellulose conversion process and the search for cheaper and effective pretreatment methodologies for each biomass is a complex but fundamental task. Here, we used a 2ν5-1 fractional factorial design (FFD) to optimize five pretreatment variables: milling time, temperature, double treatment, chemical concentration, and pretreatment time in acid-alkali (EA) and acid-organosolv (EO) pretreatments, applied to elephant grass leaves.ResultsFFD allowed optimization of the pretreatment conditions using a reduced number of experiments and allowed the identification of secondary interactions between the factors. FFD showed that the temperature can be kept at its lower level and that the first acid step can be eliminated in both pretreatments, without significant losses to enzymatic hydrolysis. EA resulted in the highest release of reducing sugars (maximum of 205 mg/g substrate in comparison to 152 mg/g in EO and 40 mg/g in the untreated sample), using the following conditions in the alkali step: [NaOH] = 4.5% w/v; 85 °C and 100 min after ball milling the sample. The factors statistically significant (P < 0.05) in EA pretreatment were NaOH concentration, which contributes to improved hydrolysis by lignin and silica removal, and the milling time, which has a mechanical effect. For EO samples, the statistically significant factors to improved hydrolysis were ethanol and catalyst concentrations, which are both correlated to higher cellulose amounts in the pretreated substrates. The catalyst is also correlated to lignin removal. The detailed characterization of the main hemicellulosic sugars in the solids after pretreatments revealed their distinct recalcitrance: glucose was typically more recalcitrant than xylose and arabinose, which could be almost completely removed under specific pretreatments. In EA samples, the removal of hemicellulose derivatives was very dependent on the acid step, especially arabinose removal.ConclusionThe results presented herewith contribute to the development of more efficient and viable pretreatments to produce cellulosic ethanol from grass biomasses, saving time, costs and energy. They also facilitate the design of enzymatic cocktails and a more appropriate use of the sugars contained in the pretreatment liquors, by establishing the key recalcitrant polymers in the solids resulting from each processing step.

Dataset Information

Factorial design-assisted spectroscopic determination of oxybutynin hydrochloride.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets