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Principal component regression (PCR) and partial least squares with one dependent variable (PLS1) and two dependent variables (PLS2) were applied on spectral data of pharmaceutical formula containing Pseudoephedrine (PDP) and Guaifenesin (GFN). The ability to derivitize in resolved overlapping spectra chloropheniramine maleate was evaluated when multivariate methods are adopted for analysis of two component mixtures without using any chemical pretreatment. The chemometrics models were tested on an external validation dataset and finally applied to the analysis of pharmaceuticals. Significant advantages were found in analysis of the real samples when the calibration models from derivative spectra were used. It should also be mentioned that the proposed method is a simple and rapid way requiring no preliminary separation steps and can be used easily for the analysis of these compounds, especially in quality control laboratories. 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