Abstract

Analysis of multi component dosage forms poses a greater challenge for the precise and accurate determination of individual concentrations of the drugs in the mixtures without prior separation steps if conventional ultraviolet spectrophotometric methods are applied for the analysis. In this research, similar problem was identified where the estimation of lidocaine and phenazone by conventional ultraviolet methods is quite difficult because of their spectral overlapping. This problem is solved by applying the chemometric models like principal component regression and partial least squares for the analysis of individual drugs in ear drops dosage form. Two different set of mixtures namely calibration set and validation set were prepared containing the synthetic mixtures of two drugs in different non-repetitive concentration sets. Spectra of these mixtures were recorded and the wavelength range of 240-300 nm with a data interval of 2 nm was used for transforming the data in to the principal component regression and partial least squares models. The calibration set serves to optimize the model and whereas the validation serves to affirm the model accuracy. Both the developed models showed accurate predictive abilities for the determination of these drugs which was evident from the results obtained for these models. One-way analysis of variance was performed to prove that there are no significant differences in these two models for the assay determination of the drugs in the ear drops. Greenness was evaluated for this analytical method and the score indicates that the method relatively much greener which encourages the analysts to use more often than not.