Simultaneous determination of antiviral drugs in biological fluids using excitation-emission fluorescence spectroscopy and chemometrics

This study presents a new method for simultaneous determination of antiviral drugs in biological fluids using excitation-emission fluorescence (EEF) spectroscopy and N-way partial least square (N-PLS) algorithm [1]. Several methods including high performance liquid chromatography (HPLC) and ion mobility spectroscopy (IMS) were previously proposed for simultaneous determination of drugs in biological fluids. These methods suffer from the need for large sample volumes, being time-consuming and a need for extensive pretreatment protocols. Despite extraction and chromatographic methods, EEF is fast, green and can be used for quantification of the analytes in the presence of uncalibrated interferents (i.e. second-order advantage) [3].In this study, the central composite design (CCD) was used for construction of the calibration samples for ensuring orthogonality of the concentration of the analytes. We used an extension of the variable importance in projection (VIP) method to three-way arrays in order to select the most relevant wavelengths [2]. Three important antiviral drugs including Aciclovir, Valaciclovir and Ribavirin were used as model compounds to test the feasibility of the proposed method. The structural similarity of the studied molecules provides efficient study design for assessing the ability of the proposed method for calibrating molecules with intense overlapping peaks. The obtained statistical parameters in terms of regression coefficient (R2) and root mean square error (RMSE) were satisfactory for the calibration and prediction sets. Table 1 shows R2 and RMSE values for NPLS model before after selection of important variables. The given figures of merits reveal that the proposed method could nicely calibrate the studied molecules even with small set of selected wavelengths in both excitation and emission fluorescence modes. The results revealed the superiority of the VIP-NPLS algorithm compared to NPLS and the number of selected variables reduced about two orders of magnitudes. It extensively increases the interpretability of the models which is a vital for systematic investigations in such complex interacting systems.