Robust Regression Analysis of Full Overlapping Caffeine and Pyridoxine HCl UV-Vis Spectra in Pharmaceutical Tablet

Abstract

The determination of caffeine and pyridoxine HCl in medicinal tablets has been successfully carried out. The mixture of caffeine and pyridoxine solution produces UV-Vis with full overlapping spectra. The full overlapping spectra can not be analyzed using conventional multicomponent analysis, as they do not have a distinct maximum wavelength. This research proposed a full overlapping spectra analysis using Robust regression. The regression models used in this research were based on Huber, RANSAC, and Theil-Sen Regression. Robust regression is a regression method that was not sensitive to the presence of outliers from the input or output data. Robust Regression models were trained using 25 standard solutions of caffeine and pyridoxine HCl at varied ratios. The models were validated using test solutions with known concentration ratios. The validated models were applied to determine the concentration of medicinal tablets. From this study, the recovery values of medicinal tablets obtained using Huber, RANSAC, and Theil-Sen Regression methods for caffeine were 96.94%, 97.19%, and 96.16% respectively, while the recoveries of pyridoxine HCl were 122.65%, 104.89%, and 107.48%.