F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Talanta. 2010 May 15;81(3):988-95. doi: 10.1016/j.talanta.2010.01.046. Epub 2010 Feb 1.
Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.
拉曼光谱已成为分析药物固体制剂的一种有吸引力的工具。在本研究中,它被用于确保片剂的身份。该方法的两个主要应用是在质量控制中释放最终产品和检测假冒产品。光谱库中包含了 25 个片剂产品系列,采用了一种非线性分类方法,支持向量机(SVM)。开发了两个级联校准:第一个识别产品系列,第二个指定配方。一个产品系列包含具有相同活性药物成分(API)但含量不同的不同配方。一旦 SVM 模型对片剂进行了分类,就会应用 API 峰检测和相关技术,以便为识别提供一种特定的方法,并允许在未来将假冒产品与正品区分开来。这种校准策略可以在没有关于样品的先验信息的情况下,无误地识别 25 个产品系列。因此,拉曼光谱结合化学计量学是一种快速、准确的药物片剂识别工具。