Mazurek Sylwester, Szostak Roman
Department of Chemistry, University of Wrocław, 14 F. Joliot-Curie, 50-383 Wrocław, Poland.
J Pharm Biomed Anal. 2009 Jan 15;49(1):168-72. doi: 10.1016/j.jpba.2008.10.015. Epub 2008 Nov 1.
The FT-Raman quantification of atorvastatin calcium in tablets was performed using the partial least squares (PLS), principal component regression (PCR) and counter-propagation artificial neural networks (CP-ANN) methods. To compare the predictive abilities of the elaborated models, the relative standard errors of prediction (RSEP) were calculated. The application of PLS, PCR and 6x6 CP-ANN provided models of comparable quality. RSEP error values in the range of 1.9-2.8% for calibration and validation data sets were obtained for the three procedures applied. Four commercial products containing 10, 20 or 40 mg of atorvastatin calcium per tablet were successfully quantified. Concentrations found from the Raman data analysis correlate strongly with the declared values, with a recovery of 98.5-101.3%, and with the results of reference analysis, with the recovery of 98.9-102.1%, for the different models. The proposed procedure can be a fast, precise and convenient method of atorvastatin calcium quantification in commercial tablets.
采用偏最小二乘法(PLS)、主成分回归法(PCR)和反向传播人工神经网络(CP-ANN)方法对片剂中的阿托伐他汀钙进行傅里叶变换拉曼定量分析。为比较所构建模型的预测能力,计算了预测相对标准误差(RSEP)。PLS、PCR和6×6 CP-ANN的应用提供了质量相当的模型。对于所应用的三种方法,校准和验证数据集的RSEP误差值在1.9%至2.8%范围内。成功定量了每片含10、20或40 mg阿托伐他汀钙的四种商业产品。从拉曼数据分析得到的浓度与宣称值高度相关,不同模型的回收率为98.5%至101.3%,与参考分析结果的回收率为98.9%至102.1%。所提出的方法可为商业片剂中阿托伐他汀钙的定量分析提供一种快速、精确且便捷的方法。