(301c) Development of a High-Fidelity Digital Twin Using DEM for Evaluating Continuous Manufacturing Control Approaches | AIChE

(301c) Development of a High-Fidelity Digital Twin Using DEM for Evaluating Continuous Manufacturing Control Approaches


Remmelgas, J., RCPE GmbH
Toson, P., RCPE
Matic, M., RCPE GmbH
Hörmann-Kincses, T. R., Research Center Pharmaceutical Engineering GmbH
Beretta, M., Research Center Pharmaceutical Engineering Gmbh
Rehrl, J., RCPE Gmbh
O'Connor, T., U.S. Food and Drug Administration
Koolivand, A., Food and Drug Administration
Tian, G., FDA
Krull, S. M., Office of Testing and Research, U.S. Food and Drug Administration
Khinast, J. G., Graz University of Technology
Pharmaceutical process development (batch or continuous) includes multiple particle processing steps that could affect the drug product quality such as content uniformity. Such processes are normally developed by extensive experimental research, however, by narrow material variation and within a small design space. Thus, in silico modelling and high-fidelity digital twins can be beneficial for the industry to explore larger design space, including in-depth process development, and more optimization studies through numerous virtual experiments and by quantitative evaluation of the outcomes.

The Research Center Pharmaceutical Engineering (Austria) supported by the U.S. FDA have recently started a project to develop an approach for assessing drug manufacturing control strategies based on high-fidelity digital twins taking a direct compression line as a use-case. The high-fidelity digital twin platform is designed based on typical pharmaceutical materials, equipment, processes, and drug products. These components will be simulated in the digital twin tool by verified numerical methods and algorithms [1,2,3]. The model accuracy and simulation results will be validated by experimental methods to ensure the model predictability considering different direct compression lines.

This work presents the project workflow and the preliminary results. This includes the characterization of a common blend widely used in the pharmaceutical industry, introducing material properties for the blend in the Discrete Element Model (DEM), the workflow for calibrating the DEM contact parameters, and finally, the results of an investigation related to a study of a horizontal continuous mixer. The results of the mixer simulations cover design space studies such as different mixer throughputs and rotational speeds. Furthermore, materials are tracked in each unit operation by means of Residence Time Distribution (RTD), which can be used as a vital part of the control strategy. Combining RTD curves of individual units via convolution integrals, the line RTD curve can be calculated, which further describes propagation and attenuation of disturbances through a continuous manufacturing line for material traceability.


This abstract reflects the views of the authors and should not be constructed to represent FDA’s views or policies.


[1] Toson et al., 2018. "Detailed modeling and process design of an advanced continuous powder mixer". Int J Pharm 552, 288–300. https://doi.org/10.1016/j.ijpharm.2018.09.032

[2] Toson et. Al., 2019. “Explicit Residence Time Distribution of a Generalised Cascade of Continuous Stirred Tank Reactors for a Description of Short Recirculation Time (Bypassing)”, Processes 2019, 7(9), 615; https://doi.org/10.3390/pr7090615

[3] Toson et al. 2021, "Continuous Powder Mixing Technology: Validation of the DEM Model". submitted to J Pharm Sci.