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基于分光光度信号的风险评估用于环保分析场景中,以估算药物制剂中的卡维地洛和氢氯噻嗪。

Risk assessment based on spectrophotometric signals used in eco-friendly analytical scenarios for estimation of carvedilol and hydrochlorothiazide in pharmaceutical formulation.

机构信息

Pharmaceutical Chemistry Department, Faculty of Pharmacy, Future University in Egypt, Cairo, 11835, Egypt.

Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, El-Kasr El-Aini Street, Cairo, 11562, Egypt.

出版信息

Sci Rep. 2024 Aug 23;14(1):19657. doi: 10.1038/s41598-024-69746-0.

DOI:10.1038/s41598-024-69746-0
PMID:39179633
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11343851/
Abstract

Special attention is given to the pharmacological treatment of combined medication of Carvedilol and hydrochlorothiazide which is the most effective and the most beneficial therapy for hypertensive patients with diabetes and various metabolic comorbidities. This work represents spectrophotometric platform scenarios based on factorized spectrum (FS) using interpoint data difference resolution scenarios (IDDRS) coupled with spectrum subtraction method (SS) for the concurrent quantification of carvedilol (CAR) and hydrochlorothiazide (HCT) when present together in a combination without the need for any initial physical separation steps. This IDD resolution scenario based on manipulating the zero-order spectra (D) of both drugs in the mixture with various spectral features at different wavelength regions (200-400 nm), region I (220-250 nm), region II (240-300 nm) and region III (270-320 nm) via absorbance resolution (AR) and induced absorbance resolution (IAR) methods coupled with corresponding spectrum subtraction (SS). The calibration curves were established across the linearity ranges of 2.0-12.0 µg/mL at 242.50 nm and 4.0-40.0 µg/mL at 285.5 nm for CAR and 1.0-11.0 µg/mL at 226.10 nm and 2.0-20.0 µg/mL at 270.5 nm for HCT. Moreover, methods' validation was confirmed via ICH guidelines. A Multicenter comparison between sensitivity, specificity in respect resolution sequence were applied using different wavelength regions with various concentration ranges was applied and finally spectral resolution recommendation is issued and cumulative validation score (CVS) is calculated as an indicator in the risk analysis. In quality control laboratories, the studied approaches are applicable for conducting analysis on the mentioned drugs. In addition, the selection of spectrophotometry aligns with the principles of green analytical chemistry, an approach that resonates with the overarching theme of minimizing environmental impact. Via four metric tools named: analytical greenness (AGREE), green analytical procedure index (GAPI), analytical eco-scale, and national environmental method index (NEMI), methods' greenness profile was guaranteed.

摘要

特别关注卡维地洛和氢氯噻嗪联合用药的药理学治疗,这是糖尿病和各种代谢合并症高血压患者最有效和最有益的治疗方法。这项工作代表了基于因子分解光谱 (FS) 的分光光度平台场景,使用多点数据差分解决方案 (IDDRS) 结合光谱减法 (SS),用于同时定量存在于组合中的卡维地洛 (CAR) 和氢氯噻嗪 (HCT),而无需任何初始物理分离步骤。这种基于 IDD 分辨率方案通过在混合物中操纵两种药物的零阶光谱 (D) 来实现,混合物在不同波长区域 (200-400nm)、区域 I (220-250nm)、区域 II (240-300nm) 和区域 III (270-320nm) 具有各种光谱特征,通过吸光度分辨率 (AR) 和诱导吸光度分辨率 (IAR) 方法与相应的光谱减法 (SS) 相结合。在 242.50nm 处的线性范围为 2.0-12.0µg/mL 和 285.5nm 处的 4.0-40.0µg/mL 为 CAR 建立校准曲线,在 226.10nm 处的线性范围为 1.0-11.0µg/mL 和 270.5nm 处的 2.0-20.0µg/mL 为 HCT 建立校准曲线。此外,方法的验证是通过 ICH 指南确认的。通过在不同波长区域应用不同浓度范围,应用了多中心比较方法,在灵敏度、分辨率序列特异性方面进行了比较,最后提出了光谱分辨率建议,并计算了累积验证评分 (CVS) 作为风险分析中的指标。在质量控制实验室中,所研究的方法适用于对所述药物进行分析。此外,分光光度法的选择符合绿色分析化学的原则,这一方法与最大限度减少环境影响的总体主题相一致。通过四个名为分析绿色度 (AGREE)、绿色分析程序指数 (GAPI)、分析生态标度和国家环境方法指数 (NEMI) 的度量工具,保证了方法的绿色度概况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/05b363ef8109/41598_2024_69746_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/9ae71db79c06/41598_2024_69746_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/05b363ef8109/41598_2024_69746_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/9ae71db79c06/41598_2024_69746_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/b59fddd06890/41598_2024_69746_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/7f08d5619e72/41598_2024_69746_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/3ec18f4de741/41598_2024_69746_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4378/11343851/05b363ef8109/41598_2024_69746_Fig5_HTML.jpg

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