采用化学计量学的拉曼光谱和近红外光谱法鉴别山莨菪碱片
Identification of anisodamine tablets by Raman and near-infrared spectroscopy with chemometrics.
作者信息
Li Lian, Zang Hengchang, Li Jun, Chen Dejun, Li Tao, Wang Fengshan
机构信息
Key Laboratory of Chemical Biology of Natural Products (Ministry of Education), Institute of Biochemical and Biotechnological Drug, School of Pharmaceutical Sciences, Shandong University, No. 44 Wenhuaxi Road, Jinan 250012, China.
Shandong Institute for Food and Drug Control, No. 2749, Xinluo Avenue, High-tech Zone, Jinan 250101, China.
出版信息
Spectrochim Acta A Mol Biomol Spectrosc. 2014 Jun 5;127:91-7. doi: 10.1016/j.saa.2014.02.022. Epub 2014 Feb 22.
Vibrational spectroscopy including Raman and near-infrared (NIR) spectroscopy has become an attractive tool for pharmaceutical analysis. In this study, effective calibration models for the identification of anisodamine tablet and its counterfeit and the distinguishment of manufacturing plants, based on Raman and NIR spectroscopy, were built, respectively. Anisodamine counterfeit tablets were identified by Raman spectroscopy with correlation coefficient method, and the results showed that the predictive accuracy was 100%. The genuine anisodamine tablets from 5 different manufacturing plants were distinguished by NIR spectroscopy using partial least squares discriminant analysis (PLS-DA) models based on interval principal component analysis (iPCA) method. And the results showed the recognition rate and rejection rate were 100% respectively. In conclusion, Raman spectroscopy and NIR spectroscopy combined with chemometrics are feasible and potential tools for rapid pharmaceutical tablet discrimination.
包括拉曼光谱和近红外（NIR）光谱在内的振动光谱已成为药物分析中一种有吸引力的工具。在本研究中，分别基于拉曼光谱和近红外光谱建立了用于鉴别山莨菪碱片及其假药以及区分生产厂家的有效校准模型。采用相关系数法通过拉曼光谱鉴别山莨菪碱假药，结果表明预测准确率为100%。利用基于区间主成分分析（iPCA）方法的偏最小二乘判别分析（PLS-DA）模型，通过近红外光谱区分了来自5个不同生产厂家的正品山莨菪碱片。结果表明识别率和拒识率均分别为100%。总之，拉曼光谱和近红外光谱结合化学计量学是快速鉴别药物片剂的可行且有潜力的工具。
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