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近红外光谱结合化学计量学快速无损鉴别掺伪胶囊。

Rapid and nondestructive identification of adulterate capsules by NIR spectroscopy combined with chemometrics.

机构信息

College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.

College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.

出版信息

J Pharm Biomed Anal. 2023 Oct 25;235:115597. doi: 10.1016/j.jpba.2023.115597. Epub 2023 Jul 22.

Abstract

This study aims to develop a rapid and non-destructive method to identify counterfeit and substandard drugs, addressing the critical need for better quality control in drug production. According to the reasons for counterfeit products in actual production, the commonly used solid preparation excipients such as HPMC, MCC, Mg-St and Pregelatinized Starch, as well as three chemical drugs with similar efficacy to Guizhi-Fuling (GZFL) Capsule as adulterants, including Aspirin, Ibuprofen and Sinomenine Hydrochloride were selected and designed as adulteration samples with different levels of adulteration. NIR spectra were collected in a non-invasive mode and analyzed by one-class classification methods. The feasibility of using Near-infrared (NIR) spectroscopy as a detection method to qualitatively identify adulterated samples was explored at three packaging levels of powder, intact capsules and capsules in PVC. The differences between the samples were analyzed by NIR spectra comparison, cluster analysis and principal component analysis. The performance of SVM, OCPLS and DD-SIMCA models in dealing with the authentication of genuine and counterfeit products was established and compared. The results show that the spectra contain sample information and the adulterated samples could be discriminated correctly by established models. Moreover, applying appropriate spectral preprocessing methods can further improve the model's performance. In addition, a PLS regression model was developed to predict the adulteration levels of the three packing level samples, which yielded satisfactory results. This study highlights the potential of NIR spectroscopy combined with Chemometrics as a rapid and non-destructive testing analysis method to accurately identify counterfeit and substandard drugs, thereby ensuring drug quality.

摘要

本研究旨在开发一种快速、无损的方法来识别假冒伪劣药品,以满足药品生产中更好质量控制的迫切需求。根据实际生产中假冒产品的原因,选择并设计了常用的固体制剂辅料如 HPMC、MCC、Mg-St 和预胶化淀粉,以及三种与桂枝茯苓胶囊(GZFL)疗效相似的化学药物作为掺杂物,包括阿司匹林、布洛芬和盐酸青藤碱,作为不同掺杂物水平的掺杂物。采用非侵入式模式采集近红外(NIR)光谱,并通过单类分类方法进行分析。探讨了近红外光谱法作为一种检测方法,定性识别粉末、完整胶囊和 PVC 胶囊三种包装水平的掺杂物样品的可行性。通过 NIR 光谱比较、聚类分析和主成分分析来分析样品之间的差异。建立并比较了 SVM、OCPLS 和 DD-SIMCA 模型在鉴别真伪产品方面的性能。结果表明,光谱包含样品信息,建立的模型可以正确区分掺杂物样品。此外,应用适当的光谱预处理方法可以进一步提高模型的性能。此外,还开发了一个 PLS 回归模型来预测三种包装水平样品的掺杂物水平,结果令人满意。本研究强调了近红外光谱结合化学计量学作为一种快速、无损的测试分析方法,可用于准确识别假冒伪劣药品,从而确保药品质量。

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