TY - JOUR
T1 - Development of a high-fidelity digital twin using the discrete element method for a continuous direct compression process. Part 2. Validation of calibration workflow
AU - Jajcevic, Dalibor
AU - Remmelgas, Johan
AU - Toson, Peter
AU - Matić, Marko
AU - Hörmann-Kincses, Theresa
AU - Beretta, Michela
AU - Rehrl, Jakob
AU - Poms, Johannes
AU - Boehling, Peter
AU - O'Connor, Thomas
AU - Koolivand, Abdollah
AU - Tian, Geng
AU - Krull, Scott M.
AU - Khinast, Johannes G.
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/12/5
Y1 - 2024/12/5
N2 - 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.
AB - 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.
KW - Continuous manufacturing
KW - Control strategy
KW - DEM calibration
KW - DEM simulation
KW - Digital twin
KW - Residence time distribution
UR - http://www.scopus.com/inward/record.url?scp=85206437404&partnerID=8YFLogxK
U2 - 10.1016/j.ijpharm.2024.124797
DO - 10.1016/j.ijpharm.2024.124797
M3 - Article
C2 - 39368673
AN - SCOPUS:85206437404
SN - 0378-5173
VL - 666
JO - International Journal of Pharmaceutics
JF - International Journal of Pharmaceutics
M1 - 124797
ER -