Chemometrics Assisted Spectrophotometric Method Development and Validation for Simultaneous Estimation of Abacavir, Lamivudine and Dolutegravir in Dosage Form

Abstract

Aim: Multivariate methods, particularly Classical Least Square, Inverse Least Square (ILS), Partial Least Square and Principal Component Regression are invented for the quantitation of the Abacavir sulphate (ABA), Lamivudine (LAM) and Dolutegravir sodium (DOL) in their combined tablet formulation. Materials and Methods: Chemometrics is the integration of statistical and mathematical approaches to analytical data in order to extract as much information as possible. The calibration and validation sets were built using fractional factorial design. 32 ternary mixtures of calibration sets and 16 mixtures of validation set were prepared. The absorbance data matrix was created by measuring absorbance in the range of 230 to 308 nm (Δλ = 3 nm) at 27 distinct wavelengths. The models were developed with the aid of MATLAB 2018a, Minitab 16.1.1 and MS Excel 2010. Results: The recovery values were close to 100% with low standard deviation (SD) justified the high accuracy of the proposed methods. For chemometrics approaches, the RMSECV, RMSEC, and RMSEP values produced show good accuracy and precision. The values of model diagnostic tools were lowest for ILS method. Conclusion: The ILS was shown to be the most appropriate method among produced chemometric models. The chemometric method is more accurate and precise than conventional methods as the total absorbance of the ternary mixture was measured and can be utilised in simultaneous estimation. With great recoveries and precision, the proposed approach was successfully used to the assay of formulation.