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立普妥仿制药的检测:近红外光谱和拉曼光谱结合化学计量学的比较

Detection of Lipitor counterfeits: a comparison of NIR and Raman spectroscopy in combination with chemometrics.

作者信息

de Peinder P, Vredenbregt M J, Visser T, de Kaste D

机构信息

VibSpec, Haaftenlaan 28, 4006 XL Tiel, The Netherlands.

出版信息

J Pharm Biomed Anal. 2008 Aug 5;47(4-5):688-94. doi: 10.1016/j.jpba.2008.02.016. Epub 2008 Feb 26.

Abstract

Research has been carried on the feasibility of near infrared (NIR) and Raman spectroscopy as rapid screening methods to discriminate between genuine and counterfeits of the cholesterol-lowering medicine Lipitor. Classification, based on partial least squares discriminant analysis (PLS-DA) models, appears to be successful for both spectroscopic techniques, irrespective of whether atorvastatine or lovastatine has been used as the active pharmaceutical ingredient (API). The discriminative power of the NIR model, in particular, largely relies on the spectral differences of the tablet matrix. This is due to the relative large sample volume that is probed with NIR and the strong spectroscopic activity of the excipients. PLS-DA models based on NIR or Raman spectra can also be applied to distinguish between atorvastatine and lovastatine as the API used in the counterfeits tested in this study. A disadvantage of Raman microscopy for this type of analysis is that it is primarily a surface technique. As a consequence spectra of the coating and the tablet core might differ. Besides, spectra may change with the position of the laser in case the sample is inhomogeneous. However, the robustness of the PLS-DA models turned out to be sufficiently large to allow a reliable discrimination. Principal component analysis (PCA) of the spectra revealed that the conditions, at which tablets have been stored, affect the NIR data. This effect is attributed to the adsorption of water from the atmosphere after unpacking from the blister. It implies that storage conditions should be taken into account when the NIR technique is used for discriminating purposes. However, in this study both models based on NIR spectra and Raman data enabled reliable discrimination between genuine and counterfeited Lipitor tablets, regardless of their storage conditions.

摘要

已对近红外(NIR)光谱和拉曼光谱作为快速筛选方法以区分降胆固醇药物立普妥的真品和假冒品的可行性进行了研究。基于偏最小二乘判别分析(PLS-DA)模型的分类对于这两种光谱技术似乎都是成功的,无论阿托伐他汀还是洛伐他汀被用作活性药物成分(API)。特别是,近红外模型的判别能力在很大程度上依赖于片剂基质的光谱差异。这是由于近红外探测的样品体积相对较大以及辅料的强光谱活性。基于近红外或拉曼光谱的PLS-DA模型也可用于区分阿托伐他汀和洛伐他汀,作为本研究中测试的假冒品中使用的API。拉曼显微镜用于此类分析的一个缺点是它主要是一种表面技术。因此,包衣和片剂核心的光谱可能不同。此外,如果样品不均匀,光谱可能会随激光位置而变化。然而,PLS-DA模型的稳健性被证明足够大,能够进行可靠的判别。光谱的主成分分析(PCA)表明,片剂的储存条件会影响近红外数据。这种影响归因于从泡罩包装中取出后从大气中吸附水分。这意味着在使用近红外技术进行判别时应考虑储存条件。然而,在本研究中,基于近红外光谱和拉曼数据的两种模型都能够可靠地区分立普妥真品和假冒片剂,无论其储存条件如何。

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