首页> 外文期刊>Journal of Pharmaceutical and Biomedical Analysis: An International Journal on All Drug-Related Topics in Pharmaceutical, Biomedical and Clinical Analysis >Detection of Lipitor counterfeits: a comparison of NIR and Raman spectroscopy in combination with chemometrics.
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Detection of Lipitor counterfeits: a comparison of NIR and Raman spectroscopy in combination with chemometrics.

机译:立普妥假冒产品的检测:近红外光谱和拉曼光谱与化学计量学的比较。

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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.
机译:已经进行了研究,以近红外(NIR)和拉曼光谱法作为快速筛选方法,以区分降胆固醇药物立普妥的真伪。基于偏最小二乘判别分析(PLS-DA)模型的分类,对于两种光谱技术而言似乎都是成功的,而与阿托伐他汀或洛伐他汀已被用作活性药物成分(API)无关。特别是,NIR模型的判别力在很大程度上取决于药片基质的光谱差异。这是由于用NIR探测到的样品量相对较大以及赋形剂的强光谱活性。基于NIR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,作为本研究中仿冒产品中使用的API。对于这种类型的分析,拉曼显微镜的缺点是它主要是表面技术。结果,包衣和片剂核的光谱可能不同。此外,在样品不均匀的情况下,光谱可能会随激光的位置而变化。但是,事实证明,PLS-DA模型的鲁棒性足够大,可以进行可靠的区分。光谱的主成分分析(PCA)表明,片剂存放的条件会影响NIR数据。这种影响归因于从水泡中取出后从大气中吸收水。这意味着当使用NIR技术进行区分时,应考虑存储条件。但是,在这项研究中,基于NIR光谱和拉曼数据的两个模型都能够可靠区分真伪立普妥片剂,无论其储存条件如何。

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