Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model
Towards rational scale-down and design optimization
C. Haringa (TU Delft - ChemE/Transport Phenomena)
Wenjung Tang (TU Delft - OLD BT/Cell Systems Engineering)
G. Wang (TU Delft - OLD BT/Cell Systems Engineering)
AT Deshmukh (TU Delft - OLD BT/Cell Systems Engineering)
Wouter van Winden (DSM)
Ju Chu (East China University of Technology)
Walter Van Gulik (TU Delft - OLD BT/Cell Systems Engineering)
Sef Heijnen (TU Delft - OLD BT/Cell Systems Engineering)
R. F. Mudde (TU Delft - ChemE/Transport Phenomena)
Henk J. Noorman (TU Delft - BT/Bioprocess Engineering)
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Abstract
We assess the effect of substrate heterogeneity on the metabolic response of P. chrysogenum in industrial bioreactors via the coupling of a 9-pool metabolic model with Euler-Lagrange CFD simulations. In this work, we outline how this coupled hydrodynamic-metabolic modeling can be utilized in 5 steps. (1) A model response study with a fixed spatial extra-cellular glucose concentration gradient, which reveals a drop in penicillin production rate qp of 18–50% for the simulated reactor, depending on model setup. (2) CFD-based scale-down design, where we design a 1-vessel scale down simulator based on the organism lifelines. (3) Scale-down verification, numerically comparing the model response in the proposed scale-down simulator with large-scale CFD response. (4) Reactor design optimization, reducing the drop in penicillin production by a change of feed location. (5) Long-term fed-batch simulation, where we verify model predictions against experimental data, and discuss population heterogeneity. Overall, these steps present a coupled hydrodynamic-metabolic approach towards bioreactor evaluation, scale-down and optimization.