用于智能分析化学方法的可视化GLANCE：用于索利那那-米拉比格隆组合分光光度测定的人工智能

IF 5.8 2区化学 Q2 CHEMISTRY, MULTIDISCIPLINARY

Sustainable Chemistry and Pharmacy Pub Date : 2025-08-11 DOI:10.1016/j.scp.2025.102159

Hayam M. Lotfy , Reem H. Obaydo , Aya A. Mouhamed

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引用次数: 0

摘要

本研究提出了一种智能分析化学方法，该方法将人工智能（AI）、绿色化学原理和白色分析化学框架策略性地整合在一起，用于药物分析。智能分析化学，绿色，分析性能和计算智能的协同作用，建立智能分光光度法同时测定琥珀酸索利那新（SOF）和米拉贝隆（MIR）用于膀胱过度活跃治疗。采用人工智能优化的信号差异策略来解决化合物之间的光谱重叠问题。开发了两种互补的智能分辨方法：(1)对MIR采用吸光度分辨率（AR），对SOF采用一阶导数（D1）的零窗方案；(2)对MIR采用比值提取（RE），对SOF采用吸光度变化（AV）的比值窗方案。在D1作用下，SOF在222.0 nm范围内呈2.5 ~ 25.0 μg/mL线性，AV在ΔA(217.0 ~ 238.0) nm范围内呈线性，MIR在249.0 nm范围内呈1.5 ~ 15.0 μg/mL线性。一项比较评估评估了两种策略的敏感性和特异性。计算累积验证分数（CVS）作为风险分析的指标。采用分析绿星区（AGSA）和RGB12算法对该方法的智能配置文件进行评估，确认环境、分析和实际性能与可持续发展目标（SDGs）相一致。此外，GLANCE工具（分析化学评价的图形布局）提供了12个结构化方法属性的可视化摘要。这项工作体现了智能分析化学的应用，为药品质量控制提供可持续、准确和环保的替代方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

GLANCE visualization for smart analytical chemistry methods: Artificial intelligence for spectrophotometric determination of solifenacin-mirabegron combination

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GLANCE visualization for smart analytical chemistry methods: Artificial intelligence for spectrophotometric determination of solifenacin-mirabegron combination

This study presents a smart analytical chemistry approach that strategically integrates artificial intelligence (AI), green chemistry principles, and white analytical chemistry frameworks for pharmaceutical analysis. Smart analytical chemistry, the synergy of greenness, analytical performance, and computational intelligence, was applied to develop smart spectrophotometric methods for the simultaneous determination of solifenacin succinate (SOF) and mirabegron (MIR) used in overactive bladder therapy. AI-optimized signal difference strategies were used to address spectral overlap challenges between the compounds.

Two complementary smart resolution approaches were developed: (1) a zero-window scenario using absorbance resolution (AR) for MIR and first derivative (D1) for SOF, and (2) a ratio-window scenario with ratio extraction (RE) for MIR followed by absorbance variation (AV) for SOF. SOF showed linearity from 2.5 to 25.0 μg/mL at 222.0 nm using D1 and AV at ΔA(217.0–238.0) nm, while MIR exhibited linearity at 249.0 nm from 1.5 to 15.0 μg/mL. A comparative evaluation assessed both strategies for sensitivity and specificity. A cumulative validation score (CVS) was computed to serve as an indicator in the risk analysis.

The method's smart profile was assessed using Analytical Green Star Area (AGSA) and the RGB12 algorithm, confirming balanced environmental, analytical, and practical performance aligned with Sustainable Development Goals (SDGs). Furthermore, the GLANCE tool (Graphical Layout for Analytical Chemistry Evaluation) provided a visual summary of twelve structured method attributes. This work exemplifies the application of smart analytical chemistry to deliver sustainable, accurate, and eco-friendly alternatives for pharmaceutical quality control.

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来源期刊

Sustainable Chemistry and Pharmacy Environmental Science-Pollution

CiteScore

8.20

自引率

6.70%

发文量

274

审稿时长

37 days

期刊介绍： Sustainable Chemistry and Pharmacy publishes research that is related to chemistry, pharmacy and sustainability science in a forward oriented manner. It provides a unique forum for the publication of innovative research on the intersection and overlap of chemistry and pharmacy on the one hand and sustainability on the other hand. This includes contributions related to increasing sustainability of chemistry and pharmaceutical science and industries itself as well as their products in relation to the contribution of these to sustainability itself. As an interdisciplinary and transdisciplinary journal it addresses all sustainability related issues along the life cycle of chemical and pharmaceutical products form resource related topics until the end of life of products. This includes not only natural science based approaches and issues but also from humanities, social science and economics as far as they are dealing with sustainability related to chemistry and pharmacy. Sustainable Chemistry and Pharmacy aims at bridging between disciplines as well as developing and developed countries.