Cournoyer A, Simard J-S, Cartilier L, Abatzoglou N
Université de Montréal, Faculty of Pharmacy, Montreal, Quebec.
Pharm Dev Technol. 2008;13(5):333-43. doi: 10.1080/10837450802390232.
The purpose of this study was to develop a robust and versatile near infrared (NIR) analysis protocol for the quality control of intact tablets containing two active pharmaceutical ingredients, acetylsalicylic acid (ASA) and caffeine, as well as three excipients. Reference samples were prepared and a calibration model built for each apparatus. All components of the formulation were characterized by transmission measurements with NIR spectroscopy (NIRS). The study was performed with three different Fourier transform NIR apparatuses and chemometric models. Calibration was carried out by the partial least squares regression method and a pre-processing technique to optimize the efficiency of the models. High performance liquid chromatography was the reference method for obtaining active pharmaceutical ingredient concentration values used in model building. It also served as a reference for chemometric model validation. Eighteen samples were analyzed by chemometric modeling to predict each component's concentration. Four out of five ingredients were quantified precisely with the three chemometric models developed. ASA quantification uncertainty ranges were between 1.0 and 1.1%, and the average error was less than 5% for caffeine. More than 99.9% of tablet content were analyzed and quantified. The results show that a versatile in-line or at-line NIRS method, with three different chemometric models built from three different acquisition apparatuses, can be developed without sample preparation for pharmaceutical tablet quality control of existing products.
本研究的目的是开发一种强大且通用的近红外（NIR）分析方案，用于对含有两种活性药物成分（乙酰水杨酸（ASA）和咖啡因）以及三种辅料的完整片剂进行质量控制。制备了参考样品，并为每种仪器建立了校准模型。制剂的所有成分均通过近红外光谱（NIRS）的透射测量进行表征。该研究使用了三种不同的傅里叶变换近红外仪器和化学计量学模型。通过偏最小二乘回归方法和预处理技术进行校准，以优化模型的效率。高效液相色谱法是获取用于模型构建的活性药物成分浓度值的参考方法。它还用作化学计量学模型验证的参考。通过化学计量学建模对18个样品进行分析，以预测每种成分的浓度。所开发的三种化学计量学模型精确地定量了五分之四的成分。ASA的定量不确定度范围在1.0%至1.1%之间，咖啡因的平均误差小于5%。分析和定量了超过99.9%的片剂含量。结果表明，无需对现有产品的药片片剂进行样品制备，就可以开发出一种通用的在线或离线NIRS方法，该方法基于三种不同采集仪器构建三种不同的化学计量学模型，用于药片片剂的质量控制。
