Multivariate calibration methods have proven to be helpful in interpreting complex spectral data, particularly in the simultaneous analysis of pharmaceutical mixtures. In this study, three chemometric-assisted spectrophotometric methods were developed and validated for the simultaneous assessment of flunixin meglumine (FM) and florfenicol (FF), namely, multivariate curve resolution–alternating least squares (MCR-ALS), artificial neural networks (ANNs), and partial least squares (PLS). These methods were successfully utilized to address the significant spectral overlap between FM and FF in their combined dose form, enabling simultaneous quantification without prior chromatographic separation. Statistical analysis was conducted to compare the performance of the proposed methods to that of a published HPLC method, and the results showed no significant variation in trueness or precision. The proposed methods were validated according to ICH guidelines, showing high sensitivity, low LOD and LOQ, and excellent precision (%RSD < 2.0%). Furthermore, they were evaluated for environmental sustainability using the analytical greenness (AGREE) metric and the complex modified green analytical procedure index (Complex MoGAPI), which provided a greenness score of 0.7 and a total sustainability score of 80. These results demonstrate the applicability of the proposed chemometric methods as straightforward, effective, and ecologically beneficial substitutes for regular quality control analysis.
Rahman et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: