LAUSR

Abstract The coating of tablets to prevent product degradation or control dissolution is a typical process in its production. Coating uniformity is critical for the quality of final product and batch acceptance. Therefore, the coating process needs to be optimized in order to achieve the desired uniformity and reduce manufacturing costs. Thus, understanding how process parameters such as spray properties, equipment geometry and tablet shape influence the coating process is critical for process optimization and approval by regulatory bodies. However this is a non-trivial task as obtaining information about the detailed processes in a tablet coater via experimental means is limited. Thus, computational modeling is the most feasible option to obtain information about the physical processes affecting the performance of tablet coaters. The most widely used computational method for such numerical modelling is the Discrete Element Method (DEM) where individual particles (tablets) are simulated. However, the computational cost of representing the typical shape of tablets is high for industrially relevant simulations. Thus tablet shape is typically approximated by simpler shapes such as spheres or multi spheres. Even with such simplifications, typical simulations take months to complete making it unfeasible for process optimization and design. In the last decade, the Graphical Processor Unit (GPU) has enabled large-scale simulations of tens of millions of spheres and millions of shaped particles using the XPS code. In this paper, we present an algorithm for modeling accurate bi-convex tablets that is tailored to the GPU. We firstly validate the algorithm and implementation against a number of experiments. Finally we perform a simulation of 20 million tablets in a drum coater to illustrate the usefulness of GPU computing for industrial coating applications. We found that the proposed method yields a good match against the lab scale experiments. For the industrial simulation the proposed method gave a more accurate result compared to the multi sphere approach while being significantly faster.