Comparative evaluation of different mathematical models for simultaneous UV spectrophotometric quantitative analysis of velpatasvir and sofosbuvir.
|
| Abstract |
Velpatasvir and sofosbuvir are new drugs prescribed in a combined pharmaceutical dosage form that pose a new challenge for the treatment of chronic hepatitis C. In this work, a comparative evaluation of the classical mathematical model, simultaneous equations, and the advanced mathematical model, partial least squares, for the spectrophotometric quantitative analysis of velpatasvir and sofosbuvir in bulk powder and in the new combined pharmaceutical dosage form was presented. The mathematical simultaneous equation method was used to resolve the overlap between velpatasvir and sofosbuvir. The absorbance and absorbativity values at 255 and 244.8 were used to construct two mathematical equations required for spectrophotometric quantitative analysis of the drugs under study. Partial least squares, an advanced mathematical tool dealing with the full spectral data of velpatasvir and sofosbuvir, was also introduced. An experimental design for the calibration sets and validation sets for the binary mixture of the drugs under study were created. The model was optimized based on a five-level, two-factor experimental design. Pre-processing of the spectral data was applied and resulted in the exclusion of the spectral region from 200 to 230 nm due to noise. The described methods were successfully applied to the spectrophotometric quantitative analysis of velpatasvir and sofosbuvir in Epclusa® tablets.
|
|---|---|
| Authors | Ahmed H Abdelazim, Sherif Ramzy, Ahmed M Abdelzaher, Mohammed Shahin |
| Journal | Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy (Spectrochim Acta A Mol Biomol Spectrosc) Vol. 267 Issue Pt 1 Pg. 120536 (Feb 15 2022) ISSN: 1873-3557 [Electronic] England |
| PMID | 34739999 (Publication Type: Journal Article) |
| Copyright | Copyright © 2021. Published by Elsevier B.V. |
| Chemical References |
|
| Topics |
|
Join CureHunter, for free Research Interface BASIC access!
Realize the full power of the drug-disease research graph!