Palou Anna, Cruz Jordi, Blanco Marcelo, Tomàs Jaume, de Los Ríos Joaquín, Alcalà Manel
Unitat de Química Analítica, Departament de Química, Facultat de Ciències, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain.
Escola Universitària Salessiana de Sarrià, Passeig Sant Joan Bosco, 74, 08017 Barcelona, Spain.
J Pharm Anal. 2012 Apr;2(2):90-97. doi: 10.1016/j.jpha.2011.11.003. Epub 2011 Nov 22.
The growing interest of the pharmaceutical industry in Near Infrared-Chemical Imaging (NIR-CI) is a result of its high usefulness for quality control analyses of drugs throughout their production process (particularly of its non-destructive nature and expeditious data acquisition). In this work, the concentration and distribution of the major and minor components of pharmaceutical tablets are determined and the spatial distribution from the internal and external sides has been obtained. In addition, the same NIR-CI allowed the coating thickness and its surface distribution to be quantified. Images were processed to extract the target data and calibration models constructed using the Partial Least Squares (PLS) algorithms. The concentrations of Active Pharmaceutical Ingredient (API) and excipients obtained for uncoated cores were essentially identical to the nominal values of the pharmaceutical formulation. But the predictive ability of the calibration models applied to the coated tablets decreased as the coating thickness increased.
制药行业对近红外化学成像(NIR-CI)的兴趣日益浓厚,这是因为它在药物整个生产过程的质量控制分析中非常有用(特别是其无损性质和快速的数据采集)。在这项工作中,测定了药片中主要和次要成分的浓度及分布,并获得了药片内部和外部的空间分布情况。此外,同样的近红外化学成像技术还能够对包衣厚度及其表面分布进行量化。对图像进行处理以提取目标数据,并使用偏最小二乘法(PLS)算法构建校准模型。未包衣片芯中活性药物成分(API)和辅料的浓度基本上与药物制剂的标称值相同。但是,应用于包衣片的校准模型的预测能力随着包衣厚度的增加而下降。