Development of a High-Fidelity digital twin using the discrete element method for a continuous direct compression process. Part 2. Validation of calibration workflow.

This paper is the second in a series of two that describes the application of discrete element method (DEM) and reduced order modeling to predict the effect of disturbances in the concentration of drug substance at the inlet of a continuous powder mixer on the concentration of the drug substance at the outlet of the mixer. In the companion publication, small-scale material characterization tests, a careful DEM parameter calibration and DEM simulations of the manufacturing process were used to develop a reliable RTD models. In the current work, the same calibration workflow was employed to evaluate the predictive ability of the resulting reduced-order model for an extended design space. DEM simulations were extrapolated using a Relay Race method and the cumulative RTD was accurately parameterized using the n-CSTR model. By performing experiments and simulations, a calibrated DEM model predicted the response of a continuous powder mixer to step changes in the inlet concentration of an API. Thus, carefully calibrated DEM models was used to guide and reduce experimental work and to establish an adequate control strategy. In addition, a further reduction in the computational effort was obtained by using the Relay Race method to extrapolate results. The predicted RTD curves were then parameterized to develop reduced order models and used to simulate the process in a matter of seconds. Overall, a control strategy evaluation tool based on high-fidelity DEM simulations was developed using material-sparing small-scale characterization tests.

Computational Fluid Dynamics-Discrete Element Method Modeling of an Industrial-Scale Wurster Coater.

Large-scale fluid bed coating operations using Wurster coaters are common in the pharmaceutical industry. Experimental measurements of the coating thickness are usually analyzed for just few particles. To better predict the coating uniformity of the entire batch, computational techniques can be applied for process understanding of the key process parameters that influence the quality attributes. Recent advances in computational hardware, such as graphics processing unit, have enabled simulations of large industrial-scale systems. In this work, we perform coupled computational fluid dynamics-discrete element method simulations of a large-scale coater that model the actual particle sizes. The influence of process parameters, inlet air flow rate, atomizing air flow rate, bead size distribution, and Wurster gap height is studied. The focus of this study is to characterize the flow inside the coater; eventually, this information will be used to predict the coating uniformity of the beads. We report the residence time distribution of the beads inside the Wurster column, that is, the active coating zone, which serves as a proxy for the amount of coating received by the beads per pass. The residence time provides qualitative and quantitative measurements of the particle-coating uniformity. We find that inlet air flow rate has the largest impact on the flow behavior and, hence, the coating uniformity.