Application of machine learning assisted multi-variate UV spectrophotometric models augmented by kennard stone clustering algorithm for quantifying recently approved nasal spray combination of mometasone and olopatadine along with two genotoxic impurities: comprehensive sustainability assessment - Abbas, Ahmed Emad F.; Gamal, Mohammed; Naguib, Ibrahim A.; Halim, Michael K.; Said, Basmat Amal M.; Ghoneim, Mohammed M.; Mansour, Mohmeed M. A.; Salem, Yomna A. (BMC chemistry, 2025)
Keywords: Algorithms; Calibration; Chemistry; Chemistry and machine learning; Chemistry and Materials Science; Chemistry/Food Science; Chemometrics; Clustering; Cost effectiveness; Design of experiments; Footprint analysis; Genetic algorithms; Genotoxicity; Greenness whiteness and blueness evaluation; Impurities; Kennard stone clustering algorithm; Least squares; Machine learning; Machine learning models; Mixtures; Mometasone and olopatadine; Pharmaceuticals; Quality control; Quality standards; Robustness; Solvents; Solvents selection tool and spider charts; Spectrophotometry; Sustainability; Sustainable development; Toluene; Machine learning models; Kennard stone clustering algorithm; Mometasone and olopatadine; Greenness whiteness and blueness evaluation; Solvents selection tool and spider charts