Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt.
Analytical Chemistry Department, Faculty of Pharmacy, October 6 University, 6 October City, Giza 12585, Egypt.
Spectrochim Acta A Mol Biomol Spectrosc. 2023 Dec 5;302:123161. doi: 10.1016/j.saa.2023.123161. Epub 2023 Jul 16.
A novel diffuse reflectance fourier transform infrared spectroscopic method accompanied by chemometrics was optimized to fulfill the white analytical chemistry and green analytical chemistry principles for the quantification of cinnarizine and piracetam for the first time without any prior separation in their challenging pharmaceutical preparation, which has a pretty substantial difference in the concentration of cinnarizine/piracetam (1:16). Furthermore, the suggested method was used for cinnarizine/piracetam dissolution testing as an effective alternative to traditional methods. For the cinnarizine/piracetam dissolution tests, we used a dissolution vessel with 900 mL of phosphate buffer pH 2.5 at 37 °C ± 0.5 °C, then the sampling was carried out by frequent withdrawal of 20 µl samples from the dissolution vessel at a one-minute interval, over one hour, then representative fourier transform infrared spectra were recorded. To create a partial-least-squares regression model, a fractional factorial design with 5 different levels and 2 factors was used. This led to the creation of 25 mixtures, 15 as a calibration set and 10 as a validation set, with varying concentration ranges: 1-75 and 16-1000 μg/mL for cinnarizine/piracetam, respectively. Upon optimization of the partial-least-squares regression model, in terms of latent variables and spectral region, root mean square error of cross-validation of 0.477 and 0.270, for cinnarizine/piracetam respectively, were obtained. The optimized partial-least-squares regression model was further validated, providing good results in terms of recovery% (around 98 to 102 %), root mean square error of prediction (0.436 and 3.329), relative root mean square error of prediction (1.210 and 1.245), bias-corrected mean square error of prediction (0.059 and 0.081), and limit of detection (0.125 and 2.786) for cinnarizine/piracetam respectively. Ultimately, the developed method was assessed for whiteness, greenness, and sustainability using five assessment tools. the developed method achieved a greener national environmental method index and complementary green analytical procedure index quadrants with higher eco-scale assessment scores (91), analytical greenness metric scores (0.87), and red-greenblue 12 algorithm scores (89.7) than the reported methods, showing high practical and environmental acceptance for quality control of cinnarizine/piracetam.
一种新的漫反射傅里叶变换红外光谱法结合化学计量学方法被优化,以满足白色分析化学和绿色分析化学原则,首次在没有任何预先分离的情况下对其具有挑战性的药物制剂进行定量分析,该制剂中辛那嗪和吡拉西坦的浓度差异很大(1:16)。此外,该方法还用于辛那嗪/吡拉西坦的溶出度测试,作为传统方法的有效替代方法。对于辛那嗪/吡拉西坦的溶出度测试,我们使用一个装有 900 毫升磷酸盐缓冲液 pH2.5 的溶出容器,在 37°C±0.5°C 的温度下进行,然后通过频繁从溶出容器中取出 20μl 样品,在一小时内每隔一分钟进行一次取样,然后记录代表性的傅里叶变换红外光谱。为了创建偏最小二乘回归模型,使用具有 5 个不同水平和 2 个因素的分因子设计。这导致创建了 25 种混合物,15 种作为校准集,10 种作为验证集,浓度范围分别为 1-75μg/mL 和 16-1000μg/mL。在对偏最小二乘回归模型进行优化时,分别获得了辛那嗪/吡拉西坦的交叉验证均方根误差 0.477 和 0.270 的潜变量和光谱区域。进一步验证了优化的偏最小二乘回归模型,在回收率%(约 98-102%)、预测均方根误差(0.436 和 3.329)、相对预测均方根误差(1.210 和 1.245)、偏置校正预测均方根误差(0.059 和 0.081)和检测限(0.125 和 2.786)方面均取得了良好的结果。最终,使用五种评估工具对所开发的方法的白色度、绿色度和可持续性进行了评估。所开发的方法在国家环境方法指数和补充绿色分析程序指数象限中达到了更绿色的水平,生态评分(91)、分析绿色度指标评分(0.87)和红绿蓝 12 算法评分(89.7)均高于报道的方法,显示出对辛那嗪/吡拉西坦质量控制的高度实际和环境接受度。