Ecological multivariate assisted spectrophotometric methods for determination of antipyrine and benzocaine HCl in presence of antipyrine official impurity and benzocaine HCl degradant: toward greenness and whiteness
Khadiga M. Kelani, Maha A. Hegazy, Amal M. Hassan, Ahmed H. Nadim
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引用次数: 0
Abstract
A simple and green chemometrics-assisted spectrophotometric technique has beendeveloped and validated for the determination of antipyrine (ANT) and benzocaine HCl (BEN) along with the official impurity of ANT, antipyrine impurity A (ANT imp-A), and the degradation product of BEN, p-amino benzoic acid (PABA), in their quaternary mixture. Three models were developed and compared: partial least squares (PLS), artificial neural networks (ANN), and multivariate curve resolution-alternating least squares (MCR-ALS) where the four studied drugs were successfully quantified. The quantitative determination of the studied drugs was assessed using percentage recoveries, standard errors of prediction, and root mean square errors of prediction. The ANN model demonstrated the lowest error and the best correlation making it the most accurate method for analysis. The models were constructed in the ranges of 5.0–9.0 µg mL−1 for ANT, 1.0–5.0 µg mL−1 for BEN, 0.5–2.5 µg mL−1 for ANT imp-A, and 0.25–1.25 µg mL−1 for PABA. The established models successfully determined ANT, BEN, ANT imp-A, and PABA with detection limits of 0.312, 0.178, 0.093, and 0.042 µg mL−1 for PLS, 0.185, 0.085, 0.001, and 0.034 µg mL−1 for ANN; and 0.473, 0.240, 0.073, and 0.069 µg mL−1 for MCR-ALS, respectively. The greenness and the whiteness of the proposed method were assessed using two green evaluating approaches: analytical Eco-scale, and AGREE, along with one white analytical chemistry evaluating tool, RGB. The three proposed models were successfully applied for determination of ANT and BEN in their pharmaceutically co-formulated dosage forms. They are also recommended for stability assays and purity testing of these drugs in quality control laboratories.
建立了一种简单的绿色化学计量辅助分光光度法,用于测定安替比林(ANT)和苯佐卡因HCl (BEN)及其官方杂质ANT,安替比林杂质A (ANT impa)和BEN的降解产物对氨基苯甲酸(PABA)。建立了偏最小二乘法(PLS)、人工神经网络(ANN)和多变量曲线解析-交替最小二乘法(MCR-ALS)三种模型,并对四种药物进行了定量分析。采用回收率、预测标准误差和预测均方根误差对所研究药物的定量测定进行评估。人工神经网络模型的误差最小,相关性最好,是最准确的分析方法。ANT的构建范围为5.0-9.0µg mL - 1, BEN为1.0-5.0µg mL - 1, ANT imp-A为0.5-2.5µg mL - 1, PABA为0.25-1.25µg mL - 1。建立的模型成功地检测了ANT、BEN、ANT impa和PABA, PLS的检出限分别为0.312、0.178、0.093和0.042µg mL - 1, ANN的检出限分别为0.185、0.085、0.001和0.034µg mL - 1;MCR-ALS分别为0.473、0.240、0.073和0.069µg mL−1。采用两种绿色评价方法:分析生态尺度和AGREE,以及一种白色分析化学评价工具RGB,对所提出方法的绿色度和白度进行了评估。所建立的三种模型均成功地应用于ANT和BEN共配制剂型的测定。它们也被推荐用于质量控制实验室中这些药物的稳定性测定和纯度检测。
期刊介绍:
BMC Chemistry, formerly known as Chemistry Central Journal, is now part of the BMC series journals family.
Chemistry Central Journal has served the chemistry community as a trusted open access resource for more than 10 years – and we are delighted to announce the next step on its journey. In January 2019 the journal has been renamed BMC Chemistry and now strengthens the BMC series footprint in the physical sciences by publishing quality articles and by pushing the boundaries of open chemistry.