Abdelazim Ahmed H, Ramzy Sherif, Abdelzaher Ahmed M, Shahin Mohammed
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Cairo, Egypt.
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Cairo, Egypt.
Spectrochim Acta A Mol Biomol Spectrosc. 2022 Feb 15;267(Pt 1):120536. doi: 10.1016/j.saa.2021.120536. Epub 2021 Oct 28.
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.
维帕他韦和索磷布韦是以复方制剂形式开具的新药,给慢性丙型肝炎的治疗带来了新挑战。在本研究中,对经典数学模型(联立方程法)和先进数学模型(偏最小二乘法)用于原料药及新型复方制剂中维帕他韦和索磷布韦的分光光度法定量分析进行了比较评估。采用数学联立方程法解决维帕他韦和索磷布韦之间的光谱重叠问题。利用255和244.8处的吸光度及吸收系数值构建了所研究药物分光光度法定量分析所需的两个数学方程。还引入了偏最小二乘法,这是一种处理维帕他韦和索磷布韦全光谱数据的先进数学工具。针对所研究药物的二元混合物创建了校准集和验证集的实验设计。基于五级二因素实验设计对模型进行了优化。对光谱数据进行了预处理,由于噪声排除了200至230nm的光谱区域。所描述的方法成功应用于Epclusa®片剂中维帕他韦和索磷布韦的分光光度法定量分析。