A Robust Ph-Based Second-Order Spectrophotometric Method for the Analysis of Four Anti-Hiv Drugs in Pharmaceutical Formulations Publisher Pubmed



Eshlaqi S N ; Khoshayand M R ; Dalali N ; Zade S V ; Abdollahi H
Source: Scientific reports Published:2026

Abstract

A robust pH-based second-order spectrophotometric strategy combined with parallel factor analysis (PARAFAC) was developed for the simultaneous determination of elvitegravir (EVG), cobicistat (COBI), emtricitabine (FTC), and tenofovir disoproxil fumarate (TDF) in pharmaceutical formulations. The proposed approach exploits pH-induced spectral variations arising from acid-base equilibria to generate structured second-order data suitable for multi-way calibration. Due to severe spectral overlap and equilibrium-related rank deficiency, separate PARAFAC models were developed for each analyte using calibration sets composed of single-component and binary mixtures, while independent quaternary mixtures were employed for external validation. The resulting three-way pH-spectral datasets were analyzed using constrained PARAFAC decomposition to resolve chemically meaningful spectral, pH-profile, and concentration-related loadings. Quantitative prediction was achieved through pseudo-univariate calibration based on the summed sample-mode scores associated with the protonated and deprotonated species of each analyte. The optimized models provided satisfactory analytical performance with root mean square errors of prediction (RMSEP) of 0.27, 0.62, 0.18, and 1.73 µg mL⁻¹ for EVG, COBI, FTC, and TDF, respectively. Good linearity, low detection limits, acceptable precision, and satisfactory recoveries were obtained for all analytes. The proposed strategy successfully preserved the second-order advantage, enabling reliable quantification in the presence of uncalibrated tablet excipients without prior separation. In addition to its satisfactory predictive capability, the method provides a simple, low-cost, and experimentally accessible alternative to chromatographic approaches for multicomponent pharmaceutical analysis. © 2026. The Author(s).