Abstract：
BACKGROUND: There is an increasing interest of scientific community in developing innovative methodologies for their analysis needs within green analytical chemistry framework. UV spectrophotometry is one of the most promising eco-friendly methods, which is integrated with advanced chemometric tools to enhance the selectivity of the analysis of complex mixtures with severe overlapped signals.
OBJECTIVE: Simultaneous determination of a triple-combination of pseudoephedrine hydrochloride (PSE), carbinoxamine maleate (CRX), and paracetamol (PAR) using an artificial intelligence system and multivariate calibration methods. This combination is recently recommended for COVID-19 home-treated patients as part of a symptomatic treatment.
METHODS: Namely, the suggested models are: Artificial Neural Networks, Partial Least Squares, and Principal Component Regression. The proposed algorithms were optimized and developed with the aid of a five-level, three-factor experimental design.
RESULTS: The investigated methods were applied over the concentration range of 100-180 μg/mL, 18-16 μg/mL, and 4-12 μg/mL for PSE, CRX, and PAR, respectively. The models validation results demonstrated excellent recoveries (around 98 to 102%), signaling the approaches outstanding resolution capacity for the cited compounds in the presence of common excipients. The outcomes of the studied methods were statistically compared to the official approaches, and no significant difference was found.
CONCLUSIONS: The suggested models were efficiently employed to determine the selected drugs in their combined tablets without any initial separation steps. The impact of these methods on the environment was evaluated via greenness tools, namely; National Environmental Method Index, Raynie and Driver\'s green assessment method, analytical Eco-Scale, Green Analytical Procedure Index, and Analytical Greenness Metric.
CONCLUSIONS: Green chemometric quality assessment of PSE, CRX, and PAR in their pure and pharmaceutical dosage forms. The established approaches are innovative, sustainable, smart, fast, selective, and cost-effective. These models are potential green nominees for routine analysis of the investigated mixture in quality control laboratories.
OBJECTIVE: Simultaneous determination of a triple-combination of pseudoephedrine hydrochloride (PSE), carbinoxamine maleate (CRX), and paracetamol (PAR) using an artificial intelligence system and multivariate calibration methods. This combination is recently recommended for COVID-19 home-treated patients as part of a symptomatic treatment.
METHODS: Namely, the suggested models are: Artificial Neural Networks, Partial Least Squares, and Principal Component Regression. The proposed algorithms were optimized and developed with the aid of a five-level, three-factor experimental design.
RESULTS: The investigated methods were applied over the concentration range of 100-180 μg/mL, 18-16 μg/mL, and 4-12 μg/mL for PSE, CRX, and PAR, respectively. The models validation results demonstrated excellent recoveries (around 98 to 102%), signaling the approaches outstanding resolution capacity for the cited compounds in the presence of common excipients. The outcomes of the studied methods were statistically compared to the official approaches, and no significant difference was found.
CONCLUSIONS: The suggested models were efficiently employed to determine the selected drugs in their combined tablets without any initial separation steps. The impact of these methods on the environment was evaluated via greenness tools, namely; National Environmental Method Index, Raynie and Driver\'s green assessment method, analytical Eco-Scale, Green Analytical Procedure Index, and Analytical Greenness Metric.
CONCLUSIONS: Green chemometric quality assessment of PSE, CRX, and PAR in their pure and pharmaceutical dosage forms. The established approaches are innovative, sustainable, smart, fast, selective, and cost-effective. These models are potential green nominees for routine analysis of the investigated mixture in quality control laboratories.
摘要：
背景：科学界对在绿色分析化学框架内开发创新方法以满足其分析需求的兴趣越来越大。紫外分光光度法是最有前途的环保方法之一,它与先进的化学计量学工具集成，以增强具有严重重叠信号的复杂混合物分析的选择性。
目的：同时测定盐酸伪麻黄碱（PSE）的三重组合，马来酸氢氧嘧啶（CRX），和扑热息痛（PAR）使用人工智能系统和多变量校准方法。这种组合最近被推荐用于COVID-19家庭治疗的患者，作为对症治疗的一部分。
方法：即，建议的模型是：人工神经网络，偏最小二乘,和主成分回归。提出的算法是在五级的帮助下进行优化和发展的，三因素实验设计。
结果：所研究的方法适用于100-180μg/mL的浓度范围，18-16μg/mL,PSE为4-12μg/mL，CRX,和PAR,分别。模型验证结果证明了良好的回收率(约98%至102%)，在常见赋形剂的存在下，所引用化合物的方法具有出色的分辨能力。将研究方法的结果与官方方法进行了统计比较，没有发现显著差异。
结论：建议的模型被有效地用于确定其组合片剂中的所选药物，而无需任何初始分离步骤。通过绿色工具评估了这些方法对环境的影响，即国家环境方法指数，雷尼和司机的绿色评估方法，分析生态尺度，绿色分析程序索引，和分析绿色指标。
结论：PSE的绿色化学计量学质量评估，CRX,和PAR的纯和药物剂型。既定的方法是创新的，可持续,聪明,快,选择性,和成本效益。这些模型是在质量控制实验室中对所研究混合物进行常规分析的潜在绿色被提名者。
目的：同时测定盐酸伪麻黄碱（PSE）的三重组合，马来酸氢氧嘧啶（CRX），和扑热息痛（PAR）使用人工智能系统和多变量校准方法。这种组合最近被推荐用于COVID-19家庭治疗的患者，作为对症治疗的一部分。
方法：即，建议的模型是：人工神经网络，偏最小二乘,和主成分回归。提出的算法是在五级的帮助下进行优化和发展的，三因素实验设计。
结果：所研究的方法适用于100-180μg/mL的浓度范围，18-16μg/mL,PSE为4-12μg/mL，CRX,和PAR,分别。模型验证结果证明了良好的回收率(约98%至102%)，在常见赋形剂的存在下，所引用化合物的方法具有出色的分辨能力。将研究方法的结果与官方方法进行了统计比较，没有发现显著差异。
结论：建议的模型被有效地用于确定其组合片剂中的所选药物，而无需任何初始分离步骤。通过绿色工具评估了这些方法对环境的影响，即国家环境方法指数，雷尼和司机的绿色评估方法，分析生态尺度，绿色分析程序索引，和分析绿色指标。
结论：PSE的绿色化学计量学质量评估，CRX,和PAR的纯和药物剂型。既定的方法是创新的，可持续,聪明,快,选择性,和成本效益。这些模型是在质量控制实验室中对所研究混合物进行常规分析的潜在绿色被提名者。
