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使用基于云的便携式NIR技术和机器学习快速检测和量化伪造的伟哥

Hervé Rais¹, Pierre Esseiva¹, Olivier Delémont¹

¹University of Lausanne, Ecole des Sciences Criminelles (School of Criminal Justice), Lausanne 1015, Switzerland.

Journal of pharmaceutical and biomedical analysis

|May 2, 2025

概括

便携式近红外 (NIR) 光谱仪提供了一个快速的现场解决方案,用于检测伪造的伟哥. 这项技术能够准确地识别假冒药物,并量化西德纳菲尔的含量,从而提高全球药物安全性.

科学领域:

分析化学分析化学
制药科学制药科学
频谱学是一种光谱学.

背景情况:

假冒药物对全球健康构成重大风险,原因是全球化和在线销售的增加.
假冒药物的非法贸易是非常有利可图的,风险很小,加剧了这个问题.

研究的目的:

开发和验证一种便携式近红外 (NIR) 光谱法,用于快速地在现场检测和量化伪造的伟哥片.
将这项技术与基于云的数据处理架构集成,以提高可访问性和效率.

主要方法:

使用便携式NIR光谱仪对真实和伪造的伟哥片进行非破坏性分析.
采用主要组件分析 (PCA),欧几里德距离和支向量机 (SVM) 来进行样本分类.
开发了机器学习模型,以准确量化西德纳菲尔含量,并根据染色体参考方法进行验证.

主要成果:

便携式NIR光谱学有效地区分了真实与伪造的伟哥药片.
开发的模型在分类样本和量化西德纳菲尔含量方面取得了很高的准确性.
该系统展示了与在线平台和现场使用的移动应用程序无集成的潜力.

结论:

便携式NIR光谱与先进的数据处理相结合,为打击伪造药物提供了快速,可靠和非破坏性的解决方案.
这项技术使监管机构和医疗保健提供者能够实时确保药物的质量和安全.
这些发现突出了药品质量控制和公共卫生保护领域的现场部署的变革性工具.

关键词:

数据处理数据处理伪造伪造伪造伪造现场分析现场分析标识标识标识标识红外光谱法红外光谱法红外光谱法药品药品药品药品药品量化量化量化量化

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