End point determination of blending process for trimebutine tablets using principle component analysis (PCA) and partial least squares (PLS) regression

Abstract

This study showed near Infrared (NIR) and Raman spectroscopy with a multivariate calibration approach were very effective to determine blend uniformity end-point. A set of 36 trimebutine samples containing magnesium stearate, stearic acid, colloidal silicon oxide, talc as excipients (0.9%∼1.8%) was acquired from six positions during blending processing with U-type blender from 0 to 30 min. Principle component analysis (PCA) with NIR and Raman spectral data was used to confirm the end-point of blending. After 30 min, the scores of principle component (PC) 1 and principle component (PC) 2 for samples moved into one point, which clearly indicated the mixture of sample became homogenous. In addition, NIR and Raman spectroscopy has been applied to the quantitative analysis of 20 trimebutine samples containing 2∼40% in mixture granules, which divided into a calibration set of 15 samples and a prediction set of 5 samples for NIR spectral data. The standard error of calibration (SEC) and standard error of prediction (SEP) are 0.15% and 0.13%, respectively using NIR while SEC and SEP of 0.95% and 0.91% are obtained using Raman spectroscopy. The results showed the NIR and Raman spectroscopy with a multivariate calibration such as PCA and PLS provide the possibility of real time monitoring of homogeneity and content uniformity during blending process.