Departament de Química, Unitat de Química Analítica, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Barcelona, Spain.
J Pharm Sci. 2010 Jan;99(1):336-45. doi: 10.1002/jps.21818.
Near infrared (NIR) spectroscopy has been used in a noninvasively mode to develop qualitative and quantitative methods for the monitoring of a wet granulation process. The formulation contained API (10%w/w) and microcrystalline cellulose and maize starch as main excipients. NIR spectra have been acquired through the glass window of the fluidizer in reflectance mode without causing interference to neither the process nor the formulation. The spectral data has been used to develop a qualitative multivariate model based on principal component analysis (PCA). This qualitative model allows the monitoring of different steps during the granulation process only using the spectral data. Also, a quantitative calibration model based on partial least squares (PLS) methodology has been obtained to predict relevant parameters of the process, such as the moisture content, particle size distribution, and bulk density. The methodology for data acquisition, calibration modeling and method application is relatively low-cost and can be easily performed on most of the pharmaceutical sites. Based on the results, the proposed strategy provides excellent results for the monitoring of granulation processes in the pharmaceutical industry.
近红外(NIR)光谱学已被用于非侵入式模式,以开发用于监测湿法造粒过程的定性和定量方法。该配方包含 API(10%w/w)和微晶纤维素以及玉米淀粉作为主要赋形剂。通过在流化床的玻璃窗口以反射模式采集 NIR 光谱,既不会干扰工艺也不会干扰配方。光谱数据已用于开发基于主成分分析(PCA)的定性多元模型。该定性模型仅使用光谱数据即可监测造粒过程中的不同步骤。此外,还获得了基于偏最小二乘法(PLS)方法的定量校准模型,以预测过程的相关参数,例如水分含量、粒度分布和堆积密度。用于数据采集、校准建模和方法应用的方法相对成本较低,并且可以在大多数制药现场轻松进行。基于结果,所提出的策略为制药行业的造粒过程监测提供了出色的结果。