Advanced chemometrics manipulation of UV-spectroscopic data for determination of three co-formulated drugs along with their impurities in different formulations using variable selection and regression model updating.

Multivariate calibration models manipulating UV-spectroscopic data of three anti-productive cough drugs namely ambroxol, guaifenesin and theophylline were constructed for the intent of simultaneous determination in presence of their impurities; guaiacol and caffeine. Both interval partial least squares (iPLS) and synergy interval partial least square (siPLS) algorithms were adopted for variables selection to extract useful information and improve the models' performance. The optimal spectral range and their combinations were assigned according to the lowest value of Root Mean Square Error of Prediction (RMSEP), Standard Error of Prediction (SEP) and Correlation Coefficient (R2). The results obtained from full spectrum PLS were compared with those obtained by iPLS and siPLS. The siPLS method exhibited better performance. The combination of four subintervals, 2, 9, 13, and 16, showed the best effect, with RMSEP of 0.1039, 0.3548 and 0.207 μg/mL, for ambroxol, guaifenesin and theophylline, respectively and correlation coefficient of 0.9999, 0.9975 and 0.9994 for ambroxol, guaifenesin and theophylline, respectively. The proposed methods were used for the simultaneous determination of the three drugs in presence of their impurities in bulk powder and in pharmaceutical formulation.