Simultaneously quantifying a novel five-component anti- migraine formulation containing ergotamine, propyphenazone, caffeine, camylofin, and mecloxamine using UV spectrophotometry and chemometric models - Abbas, Ahmed Emad F.; Abdelshafi, Nahla A.; Gamal, Mohammed; Halim, Michael K.; Said, Basmat Amal M.; Naguib, Ibrahim A.; Mansour, Mohmeed M. A.; Morshedy, Samir; Salem, Yomna A. (BMC chemistry, 2024)
Keywords: Accuracy; Algorithms; Caffeine; Chemistry; Chemistry and machine learning; Chemistry and Materials Science; Chemistry/Food Science; Chemometric models; Chemometrics; Clustering; Ellipses; Ergotamine; Errors; Kennard stone clustering algorithm; Least squares; Mean square errors; Migraine; Multi-component pharmaceutical analysis; Quality control; Spectrophotometry; Sustainability assessment; Sustainable development; Ultraviolet spectra; UV Spectrophotometry; UV Spectrophotometry; Multi-component pharmaceutical analysis; Chemometric models; Kennard stone clustering algorithm; Sustainability assessment