查看更多>>摘要：New precise, responsive and selective univariate and multivariate chemometric spectrophotometric methods were developed and validated for determination of vandetanib (VTB), dasatinib (DTB), and sorafenib (SFB) in pure form, tablets, spiked human (plasma and urine). Determination of these drugs is essential because of their therapeutic benefits. These methods included double divisor ratio spectra derivative univariate method and chemometric multivariate method including partial least-squares (PLS) and principal component regression (PCR). A novel univariate method was developed for the estimation of these drugs. This method depends on the UV-Spectrophotometric data for simultaneous analysis of a ternary overlapped mixture. The Double divisor ratio spectra derivative absorption minima at 358.4 nm was used for quantification of VTB, absorption maxima at 300.3 nm for quantification of DTB and absorption maxima at 259.8 nm for quantification of SFB. This method shown a linearity in the extent of 2-9 mu g/mL for VTB and DTB and over the concentration range of 3-9 mu g/mL SFB within correlation coefficient (r2) of 0.9999. This method was successfully applied to pure form, tablet dosage form, spiked human (urine and plasma). Chemometric PLS and PCR models were found to be linear in the range of 2-9, 2-9, and 3-9 mu g/mL for VTB, DTB and SFB, respectively. These models were estimated using eighteen mixtures as calibration set and seven mixtures as validation set. In the original data, the minimum root mean square error of prediction (RMSEP) was 0.11, 0.09 and 0.09 for VTB, DTB and SFB by PLS and 0.05, 0.04 and 0.03 by PCR while in the derivative data, the RMSEP was 0.09, 0.10 and 0.09 by PLS and 0.06, 0.06 and 0.03, by PCR for VTB, DTB and SFB, respectively. These methods were applied for the determination of the drugs in pure form and dosage form. Updating PLS model permitted the determination of the VTB, DTB and SFB in spiked human urine, plasma and drug-dissolution test of their tablet. (C) 2021 Elsevier B.V. All rights reserved.
NSTL
Elsevier