Novel spectrophotometric and factor-based multivariate calibration-prediction techniques for determination of two inhibitors of hepatitis C-virus and hepatocellular carcinoma in pure, human urine, and human plasma.

Novel univariate and multivariate factor-based calibration-prediction techniques were validated for simultaneous ultraviolet spectrophotometric determination of ribavirin (RIV), daclatasvir (DAV), sofosbuvir (SOV), and sorafenib (SON) which are co-administered for treatment of hepatocellular carcinoma (HCC) that results from Hepatitis C-virus (HCV) infection in their commercial products and in biological fluids. Determination of these compounds is essential owing to their pharmacotherapeutic benefits. Due to spectral overlapping of RIV, DAV, SOV, and SON, univariate extended derivative ratio (EDR) method and multivariate partial least-squares (PLS) and principal component regression (PCR) methods were used for constructing the calibration curves. The extended derivative ratio (EDR) absorption maxima at 215 nm and minima at 310.5 nm was used for determination of RIV and DAV, respectively and absorption maxima at 240.3 nm and minima at 284.5 nm for determination of SOV and SON, respectively. The linearity was established over the range of 6-42 μg mL, 4-16 μg mL, 10-70 μg mL, and 3-9 μg mL for RIV, DAV, SOV and SON with correlation coefficient (r2) of 0.9997, 0.9997, 0.9999 and 0.9997, respectively. This method was effectively applied to pure, pharmaceutical preparations and to spiked human urine and plasma. PLS and PCR models were established for the determination of the studied drugs in the range of 6-42, 4-16, 10-70 and 3-9 μg mL for RIV, DAV, SOV, and SON, respectively. Furthermore, updating the PLS model (PLS model update) were allowed for the determination of these drugs in spiked human urine, plasma and drug-dissolution test of their tablets. The obtained results were compared to official and reported method showing that there were no significant differences. The results of applying PLS and PCR models for evaluation of RIV, DAV, SOV, and SON in human urine samples as real samples were also encouraging. It is expected that the suitable features of the proposed method make it helpful for biological and clinical applications.