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Background: Considering the environmental impact of analytical procedures necessitates replacing the polluting analytical methods with green alternatives. Objective: This study aims to develop and validate a multivariate curve resolution–alternating least-squares (MCR-ALS) method with correlation constraint for the simultaneous determination of theophylline, ambroxol, and guaifenesin as target analytes in the presence of methylparaben and propylparaben as interfering components. In addition, a partial least-squares regression (PLSR) method was also developed andoptimized. Method: The developed methods were validated according to International Conference on Harmonization guidelines and successfully applied for the quantification of the target analytes in different pharmaceutical dosage forms. Results: Figures of merit such as root mean square error of prediction, bias, standard error of prediction, and relative error of prediction for both models were calculated, and they showedsimilar and satisfactory results. Correlation coefficients ranged between 0.9988 and 0.9992, reflectinghigh predictive ability. The optimized methods werecompared with a reported HPLC method using one-wayanalysis of variance and showed no significant difference regarding accuracy and precision. Conclusions: The proposed chemometrics methods can be used as an eco-friendly alternative for chromatographic techniques for the quality control analysis of the studied mixture in different pharmaceutical dosage forms. Highlights: An MCR-ALS model was developed. The developed model was compared with a PLSR model. Both models were validated and successfully used for the determinationof a multicomponent pharmaceutical mixture. The developed method is eco-friendly, fast, reliable, and cost-effective.

journal of aoac international

Eco-Friendly Pharmaceutical Analysis of Multicomponent Drugs Coformulated in Different Dosage Forms Using Multivariate Curve Resolution and Partial Least Squares: A Comparative Study