Comparative ANNs with Different Input Layers and GA-PLS Study for Simultaneous Spectrofluorimetric Determination of Melatonin and Pyridoxine HCl in the Presence of Melatonin’s Main Impurity

Melatonin (MLT) has many health implications, therefore it is important to develop specific analytical methods for the determination of MLT in the presence of its main impurity, N-{2-[1-({3-[2-(acetylamino)ethyl]-5-methoxy-1H-indol-2-yl}methyl)-5-methoxy-1H-indol-3-yl]ethyl}acetaamide (DMLT) and pyridoxine HCl (PNH) as a co-formulated drug. This work describes simple, sensitive, and reliable four multivariate calibration methods, namely artificial neural network preceded by genetic algorithm (GA-ANN), principal component analysis (PCA-ANN) and wavelet transform procedures (WT-ANN) as well as partial least squares preceded by genetic algorithm (GA-PLS) for the spectrofluorimetric determination of MLT and PNH in the presence of DMLT. Analytical performance of the proposed methods was statistically validated with respect to linearity, accuracy, precision and specificity. The proposed methods were successfully applied for the assay of MLT in laboratory prepared mixtures containing up to 15% of DMLT and in commercial MLT tablets with recoveries of no less than 99.00%. No interference was observed from common pharmaceutical additives and the results compared favorably with those obtained by a reference method.