SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION OF PHENYLEPHRINE HYDROCHLORIDE AND NAPHAZOLINE HYDROCHLORIDE IN EYE DROPS BY CHEMOMETRIC TECHNIQUES AND ARTIFICIAL NEURAL NETWORK

Abstract

Three multivariate calibration-prediction techniques, partial least squares (PLS), principal component regression (PCR) and artifi cial neural networks (ANN), have been applied without separation in the spectrophotometric multi-component analysis of phenylephrine hydrochloride and naphazoline hydrochloride. A set of 25 synthetic mixtures of phenylephrine hydrochloride and naphazoline hydrochloride has been evaluated to determine the predictability of PLS, PCR and ANN. The absorbance data matrix was obtained by measuring zero-order absorbances between 230-300 nm at intervals of 3 nm. The suitability of the models was determined on the basis of root mean square error (RMSE), root mean squared cross validation error (RMSECV) and root mean squared prediction error (RMSEP) values of calibration and validation data. The results showed a very good correlation between true values and the predicted concentration values. Therefore, the methods developed can be used for routine drug analysis without chemical pre-treatment.