Virtual prototyping of wet granulation processes

Wet granulation is a multiphase process utilized to produce aggregate particles with defined properties from very fine powders. Industrial approaches to wet granulation are mainly carried out by batch processes (rotating drum, tumblers) on a basis of quality by testing. Recently, a growing interest to improve the manufacturing sites changed the paradigms to continuous processes (twin-screw, fluidized bed, extrusion) in a quality by design (QbD) approach [1] which can provide variable throughput, consistent quality and reduced operator involvement [2]. However, a QbD approach process is challenging, especially in the pharmaceutical and bio-pharmaceutical sector critical where quality attributes are stringent and numerous [3]. Empirical methods for process optimization are still predominant and yet the field is lacking a comprehensive computer model to predict wet granulation processes. Simulating these processes on the microscale using discrete particle methods (DPM) is challenging because of the large number of particles involved, which differ widely in both size and material properties. Macroscale methods, tracking only the particle bulk properties, are efficient but do not resolve disperse particle properties such as the particle size distribution (PSD), which is key information for downstream processing. Multiscale methods like population balance modeling (PBM) can track distributed properties, such as the particle size, by adding them as internal variables to the macroscale (CFD) model but they do lack information on particle dynamics. A promising solution to address these deficiencies is to develop a comprehensive DPM–PBM–CFD heterogeneous multiscale model [4] which allows exploration of virtual design spaces, see Figure 1. The DPM micro-model will run in a certain parameter space and provide particle dynamics data for the PBM macro-model to derive mechanistic kernels for macroscale simulations. New microscopic simulations are only necessary, when the parameter space has to be expanded. Constitutive modeling, utilizing the insights of this framework, can help to develop an application-specific PBM for design optimizations and enable transitioning from real to virtual prototyping of wet granulation processes.

[1] J. Rantanen, J. Khinast, The Future of Pharmaceutical Manufacturing Sciences, J. Pharm. Sci. 104 (2015) 3612–3638.
[2] A. Kumar, K. V. Gernaey, T. De Beer, I. Nopens, Model-based analysis of high shear wet granulation from batch to continuous processes in pharmaceutical production - A critical review, Eur. J. Pharm. Biopharm. 85 (2013) 814–832.
[3] P. Suresh, I. Sreedhar, R. Vaidhiswaran, A. Venugopal, A comprehensive review on process and engineering aspects of pharmaceutical wet granulation, Chem. Eng. J. 328 (2017) 785–815.
[4] Weinan, E.; Engquist, B. The Heterognous Multiscale Methods. Commun. Math. Sci. 2003, 1, 87–132.