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应用红外光谱法同时测定青霉素 G 盐:正交信号校正与径向基函数-偏最小二乘回归联合的评价。

Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression.

机构信息

Department of Chemistry, Faculty of Science, Alzahra University, Vanak, Tehran, Iran.

出版信息

Spectrochim Acta A Mol Biomol Spectrosc. 2010 Sep 1;76(5):452-7. doi: 10.1016/j.saa.2010.01.002. Epub 2010 Jan 18.

Abstract

In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

摘要

在这项研究中,通过傅里叶变换红外光谱结合化学计量学,研究了一种同时测定药物混合物中青霉素 G 盐的新方法。由于成分的分析特性相似,青霉素 G 盐的混合物是一个复杂的系统。偏最小二乘法(PLS)和径向基函数-偏最小二乘法(RBF-PLS)分别用于建立光谱和成分之间的线性和非线性关系。正交信号校正(OSC)预处理方法用于校正光谱重叠和散射效应等意外信息。为了比较 OSC 对 PLS 和 RBF-PLS 模型的影响,基于常规和 OSC 预处理光谱,建立并比较了最佳的线性(PLS)和非线性(RBF-PLS)模型。结果表明,OSC 明显增强了 RBF-PLS 和 PLS 校准模型的性能。此外,在光谱与成分之间存在某些非线性关系的情况下,OSC-RBF-PLS 给出的结果优于 OSC-PLS 模型,这表明 OSC 有助于在不消除与成分相关的非线性信息的情况下,消除线性偏差的外在偏差。最后,将化学计量学模型应用于外部数据集进行测试,并应用于分析商业化的青霉素 G 盐注射产品。

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