Multi-dimensional population balance modeling and experimental validation of continuous powder mixing processes

Abstract

It has been recognized that the application of quality by design (QbD) to continuous processing in the pharmaceutical industry leads to better process control, improved product quality and mitigates scale-up issues (Schaber et al., 2011), whereby a component of QbD involves the development quantitative model-based representation of the process. In this work a population balance model (PBM) framework has been developed to model the dynamics of a continuous powder mixing process which is an important and complex unit operation used in a pharmaceutical tablet manufacturing process. Our previous studies have shown that PBM is effective in determining the various critical quality attributes (CQAs) (relative standard deviation (RSD), API composition and residence time distribution (RTD)) associated with mixing. It can also account for the key design and process parameters such as mixer RPM, processing angle, blender dimensions and number of radial and axial compartments. The developed PBM has been quantitatively validated by fitting experimentally obtained values of the above mentioned CQAs for different operating conditions. The model is dynamic and computationally tractable compared to traditional discrete element model (DEM) representations of mixing processes. This lends credence to the use of the model as an effective tool in control and optimization of blending process and can have future implementation in designing a Process Analytical Technology (PAT) system which will allow considerable improvements on the current manufacturing framework.