Prediction of the finished tablet coating variability in pan coaters by coupling CFD-DEM and Monte Carlo simulations: Method development and validation

Abstract

We present a numerical approach to predict the long-term coating variability of tablets in pan coaters by combining coupled computational fluid dynamics-discrete element method (CFD-DEM) simulations with a Monte-Carlo method. In CFD-DEM simulations, the coater geometry, operating conditions, air flow and exact tablet shapes are directly simulated to obtain statistical distributions of tablet coating mass gain and circulation time through the spray zone. These short-term distributions (∼102 s) serve as input to a Monte Carlo (MC) method to efficiently predict the coefficient of variation in pan coaters for timescales relevant to commercial manufacture (∼104 s). These predictions achieved reasonable agreement with experimental coating thickness measurements via both the manual gauge and optical coherence tomography (OCT) from coating trials on L.B. Bohle film coaters at different scales. This method enables the application of digital tools as efficient alternatives to resource-intensive experimental trials in determining the appropriate coating process parameters.