Chemometrics-assisted spectrophotometric method development and validation for simultaneous estimation of emtricitabine, tenofovir alafenamide fumarate, and dolutegravir sodium in dosage form

Abstract

Aim: This study aims on the development of a chemometric-assisted spectroscopic method for the analysis of combined dosage form of emtricitabine (EMT), tenofovir alafenamide fumarate (TEN), and dolutegravir sodium (DOL). The use of a multivariate algorithm to analyse spectrophotometric data is a novel approach to estimating drug concentrations in formulations. Materials and Methods: The quantitative estimation of EMT, TEN, and DOL in tablets was carried out using four chemometric approaches: Classical least square (CLS), inverse least square, partial least square, and principal component regression. Thirty-two ternary mixtures of calibration sets and 16 mixtures of validation sets were prepared. The absorbance data matrix was attained by calculating absorbance at 25 different wavelengths in a range of 240–336 nm (Δλ = 4 nm). The chemometric calculations were performed using Matlab2018a and Minitab software. The developed methods were validated. Results: The great accuracy of the current study was justified by the near-perfect recovery values (100%) and low standard deviation. For chemometrics approaches, the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), and root mean square error of cross-validation (RMSECV) outcomes display decent accuracy and precision. Conclusion: The CLS approach yielded the lowest predicted residual error sum of squares, RMSEC, RMSEP, and RMSECV scores. As a result, CLS might be regarded as the best chemometric approach among all techniques utilized. The label claim determined is in excellent accordance with the mean recoveries for EMT, TEN, and DOL. So, it can be used in quality control laboratories.