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首页> 外文期刊>Talanta: The International Journal of Pure and Applied Analytical Chemistry >Headspace-gas chromatographic fingerprints to discriminate and classify counterfeit medicines
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Headspace-gas chromatographic fingerprints to discriminate and classify counterfeit medicines

机译:顶空-气相色谱指纹图谱,用于鉴别和分类假药

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摘要

Counterfeit medicines are a global threat to public health. These pharmaceuticals are not subjected to quality control and therefore their safety, quality and efficacy cannot be guaranteed. Today, the safety evaluation of counterfeit medicines is mainly based on the identification and quantification of the active substances present. However, the analysis of potential toxic secondary components, like residual solvents, becomes more important. Assessment of residual solvent content and chemometric analysis of fingerprints might be useful in the discrimination between genuine and counterfeit pharmaceuticals. Moreover, the fingerprint approach might also contribute in the evaluation of the health risks different types of counterfeit medicines pose. In this study a number of genuine and counterfeit Viagra? and Cialis? samples were analyzed for residual solvent content using headspace-GC-MS. The obtained chromatograms were used as fingerprints and analyzed using different chemometric techniques: Principal Component Analysis, Projection Pursuit, Classification and Regression Trees and Soft Indepen-dent Modelling of Class Analogy. It was tested whether these techniques can distinguish genuine pharmaceuticals from counterfeit ones and if distinct types of counterfeits could be differentiated based on health risks. This chemometric analysis showed that for both data sets PCA clearly discriminated between genuine and counterfeit drugs, and SIMCA generated the best predictive models. This technique not only resulted in a 100% correct classification rate for the discrimination between genuine and counterfeit medicines, the classification of the counterfeit samples was also superior compared to CART. This study shows that chemometric analysis of headspace-GC impurity fingerprints allows to distinguish between genuine and counterfeit medicines and to differentiate between groups of counterfeit products based on the public health risks they pose.
机译:假药对全球公共卫生构成威胁。这些药物未经质量控制,因此不能保证其安全性,质量和功效。如今,假冒药品的安全性评估主要基于对存在的活性物质的鉴定和定量。但是,对潜在的有毒二级成分(例如残留溶剂)的分析变得更加重要。残留溶剂含量的评估和指纹的化学计量分析可能有助于区分真假药品。此外,指纹方法还可能有助于评估不同类型的假药构成的健康风险。在这项研究中,有多少正品和假冒伟哥?和Cialis?使用顶空-GC-MS分析样品中的残留溶剂含量。所得色谱图用作指纹图,并使用不同的化学计量技术进行分析:主成分分析,投影追踪,分类回归树和类比的软独立模型。测试了这些技术是否可以区分正版药品和假冒药品,以及是否可以根据健康风险区分不同类型的假冒产品。这项化学计量分析表明,对于这两个数据集,PCA清楚地区分了真药和假药,而SIMCA产生了最佳的预测模型。这项技术不仅可以使真品和假冒药品的区分率达到100%正确的分类率,而且与CART相比,假冒样品的分类也更为出色。这项研究表明,顶空-GC杂质指纹的化学计量分析可以区分正品药和假冒药品,并可以根据假冒产品构成的公共健康风险来区分假冒产品组。

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