Chen Zeng-Ping, Fevotte Gilles, Caillet Alexandre, Littlejohn David, Morris Julian
Centre for Process Analytics and Control Technology, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, G1 1XL, Scotland, UK.
Anal Chem. 2008 Sep 1;80(17):6658-65. doi: 10.1021/ac800987m. Epub 2008 Jul 30.
There is an increasing interest in using Raman spectroscopy to identify polymorphic forms and monitor phase changes in pharmaceutical products for quality control. Compared with other analytical techniques for the identification of polymorphs such as X-ray powder diffractometry and infrared spectroscopy, FT-Raman spectroscopy has the advantages of enabling fast, in situ, and nondestructive measurements of complex systems such as suspension samples. However, for suspension samples, Raman intensities depend on the analyte concentrations as well as the particle size, overall solid content, and homogeneity of the solid phase in the mixtures, which makes quantitative Raman analysis rather difficult. In this contribution, an advanced model has been derived to explicitly account for the confounding effects of a sample's physical properties on Raman intensities. On the basis of this model, a unique calibration strategy called multiplicative effects correction (MEC) was proposed to separate the Raman contributions due to changes in analyte concentration from those caused by the multiplicative confounding effects of the sample's physical properties. MEC has been applied to predict the anhydrate concentrations from in situ FT-Raman measurements made during the crystallization and phase transition processes of citric acid in water. The experimental results show that MEC can effectively correct for the confounding effects of the particle size and overall solid content of the solid phase on Raman intensities and, therefore, provide much more accurate in situ quantitative predictions of anhydrate concentration during crystallization and phase transition processes than traditional PLS calibration methods.
利用拉曼光谱法识别多晶型物并监测药品中的相变以进行质量控制，这一领域正受到越来越多的关注。与其他用于识别多晶型物的分析技术（如X射线粉末衍射法和红外光谱法）相比，傅里叶变换拉曼光谱法具有能够对诸如悬浮液样品等复杂系统进行快速、原位和无损测量的优点。然而，对于悬浮液样品，拉曼强度不仅取决于分析物浓度，还取决于颗粒大小、总固体含量以及混合物中固相的均匀性，这使得拉曼定量分析相当困难。在本论文中，我们推导了一个先进的模型，以明确考虑样品物理性质对拉曼强度的混杂效应。基于该模型，我们提出了一种独特的校准策略，称为乘性效应校正（MEC），以将分析物浓度变化引起的拉曼贡献与样品物理性质的乘性混杂效应引起的贡献区分开来。MEC已应用于根据柠檬酸在水中结晶和相变过程中的原位傅里叶变换拉曼测量结果预测无水物浓度。实验结果表明，MEC能够有效地校正颗粒大小和固相总固体含量对拉曼强度的混杂效应，因此，与传统的偏最小二乘校准方法相比，能够在结晶和相变过程中提供更准确的无水物浓度原位定量预测。
