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Independent comparison study of six different electronic tongues applied for pharmaceutical analysis

机译:六种不同电子舌在药物分析中的独立比较研究

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摘要

Electronic tongue technology based on arrays of cross-sensitive chemical sensors and chemometric data processing has attracted a lot of researchers' attention through the last years. Several so far reported applications dealing with pharmaceutical related tasks employed different e-tongue systems to address different objectives. In this situation, it is hard to judge on the benefits and drawbacks of particular e-tongue implementations for R&D in pharmaceutics. The objective of this study was to compare the performance of six different e-tongues applied to the same set of pharmaceutical samples. For this purpose, two commercially available systems (from Insent and AlphaMOS) and four laboratory prototype systems (two potentiometric systems from Warsaw operating in flow and static modes, one potentiometric system from St. Petersburg, one voltammetric system from Barcelona) were employed. The sample set addressed in the study comprised nine different formulations based on caffeine citrate, lactose monohydrate, maltodextrine, saccharin sodium and citric acid in various combinations. To provide for the fair and unbiased comparison, samples were evaluated under blind conditions and data processing from all the systems was performed in a uniform way. Different mathematical methods were applied to judge on similarity of the e-tongues response from the samples. These were principal component analysis (PCA), RV' matrix correlation coefficients and Tuckeris congruency coefficients. (C) 2015 Elsevier B.V. All rights reserved.
机译:近年来,基于交叉敏感化学传感器阵列和化学计量数据处理的电子舌技术吸引了许多研究人员的注意力。迄今为止,已报道的涉及药物相关任务的一些应用程序采用了不同的电子舌系统来解决不同的目标。在这种情况下,很难判断特定的电子舌实施对药物研发的利弊。这项研究的目的是比较应用于同一组药物样品的六个不同电子舌的性能。为此,使用了两个商业上可用的系统(来自Insent和AlphaMOS)和四个实验室原型系统(两个来自华沙的电位计系统以流动和静态模式运行,一个来自圣彼得堡的电位计系统,一个来自巴塞罗那的伏安系统)。该研究中涉及的样品包括9种不同配方,分别以咖啡因柠檬酸盐,乳糖一水合物,麦芽糊精,糖精钠和柠檬酸为多种组合。为了提供公平和公正的比较,在盲目条件下评估样本,并以统一的方式对所有系统进行数据处理。应用了不同的数学方法来判断样本中电子舌反应的相似性。这些是主成分分析(PCA),RV'矩阵相关系数和Tuckeris一致性系数。 (C)2015 Elsevier B.V.保留所有权利。

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