02-09-2017, 03:28 PM
In the present study we investigated the application of near-infrared (NIR-CI) chemical images supported by chemometric modeling as a non-destructive tool to monitor and evaluate the compaction processes of rollers and tablets. Based on the preliminary risk assessment, critical process parameters (roller pressure and roller speed) and critical quality attributes (tape porosity, granule size, fines quantity, tablet tensile strength ) and a design space. Five experimental tests were carried out with different process configurations that revealed intermediates (tapes, granules) and final products (tablets) with different properties. A model based on Principal Component Analysis (PCA) of NIR images was applied to map the distribution of the porosity of the tape. The porosity distribution of the PCA-based NIR-CI-based tape was used to develop predictive models for the granule size fractions. Predictive methods with acceptable R2 values could be used to predict the particle size of the pellet. The NIR-CI partial-least squares (PLS-R) regression model was used to map and predict the chemical distribution and active compound content for the roller-compacted tapes and the corresponding pellets. In order to select the optimal process, the standard deviation of tablet tensile strength and tablet weight for each batch of tablets was considered. A strong linear correlation was established between the tensile strength of the tablet and the amount of fines and granule size, respectively. These approaches are considered to have a potentially large impact on the monitoring and quality control of manufacturing lines in continuous operation, such as roller compaction and tabletting processes.