研究目的
To develop and validate four mathematical spectrophotometric methods for the selective determination of lesinurad in the presence of its oxidative degradation product.
研究成果
The developed spectrophotometric methods successfully resolved the spectral overlap between lesinurad and its oxidative degradation product, enabling selective quantification. Validation confirmed accuracy, precision, and specificity, with successful application to pharmaceutical formulations. The methods offer a cost-effective and efficient alternative to separation techniques for quality control of lesinurad.
研究不足
The methods are specific to lesinurad and its oxidative degradation product; applicability to other compounds or degradation pathways is not evaluated. The use of ethanol as a solvent may limit compatibility with other matrices. The study relies on mathematical manipulations, which could be sensitive to spectral noise or variations in experimental conditions.
1：Experimental Design and Method Selection:
The study employed four mathematical spectrophotometric methods (ratio difference spectrophotometric, first derivative of the ratio spectra, mean centering of the ratio spectra, and continuous wavelet transform) to resolve overlapping UV absorption spectra of lesinurad and its degradation product.
2：Sample Selection and Data Sources:
Pure lesinurad and its oxidative degradation product were used, with samples prepared in ethanol. Laboratory-prepared mixtures and pharmaceutical tablets (Zurampic?) were analyzed.
3：List of Experimental Equipment and Materials:
Shimadzu 1650 Spectrophotometer, 10 mm quartz cells, ethanol (HPLC grade), hydrogen peroxide (3%), volumetric flasks, and round-bottomed flasks.
4：Experimental Procedures and Operational Workflow:
Standard solutions were prepared, UV spectra were recorded from 200-400 nm, and mathematical manipulations (e.g., ratio spectra derivation, mean centering, wavelet transform) were applied. Calibration curves were constructed, and methods were validated per ICH guidelines.
5：Data Analysis Methods:
Regression analysis for linearity, calculation of LOD and LOQ, statistical tests (t-test, F-test) for comparison with reference methods.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
