Computational Fluid Dynamics for Advanced Characterisation of Bioreactors Used in the Biopharmaceutical Industry – Part I: Literature Review

Seidel, Stefan; Schirmer, Cedric; Maschke, Rüdiger W.; Rossi, Lia; Eibl, Regine; Eibl, Dieter

doi:10.5772/intechopen.109848

Cited by 4 publications

(3 citation statements)

References 157 publications

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“…Furthermore, the specific power input can be estimated using literature values and empirical formulae, or calculated using CFD [20]. However, the specific power input is only an average value without any indication of variability in the system.…”

Section: Introductionmentioning

confidence: 99%

Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors

Seidel,

Mozaffari,

Maschke

et al. 2023

Processes

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Scaling bioprocesses remains a major challenge. Since it is physically impossible to increase all process parameters equally, a suitable scale-up strategy must be selected for a successful bioprocess. One of the most widely used criteria when scaling up bioprocesses is the specific power input. However, this represents only an average value. This study aims to determine the Kolmogorov length scale distribution by means of computational fluid dynamics (CFD) and to use it as an alternative scale-up criterion for geometrically non-similar bioreactors for the first time. In order to obtain a comparable Kolmogorov length scale distribution, an automated geometry and process parameter optimization was carried out using the open-source tools OpenFOAM and DAKOTA. The Kolmogorov–Smirnov test statistic was used for optimization. A HEK293-F cell expansion (batch mode) from benchtop (Infors Minifors 2 with 4 L working volume) to pilot scale (D-DCU from Sartorius with 30 L working volume) was carried out. As a reference cultivation, the classical scale-up approach with constant specific power input (233 W m−3) was used, where a maximum viable cell density (VCDmax) of 5.02·106 cells mL−1 was achieved (VCDmax at laboratory scale 5.77·106 cells mL−1). Through the automated optimization of the stirrer geometry (three parameters), position and speed, comparable cultivation results were achieved as in the small scale with a maximum VCD of 5.60·106 cells mL−1. In addition, even on the pilot scale, cell aggregate size distribution was seen to strictly follow a geometric distribution and can be predicted with the help of CFD with the previously published correlation.

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Section: Introductionmentioning

confidence: 99%

Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors

Seidel,

Mozaffari,

Maschke

et al. 2023

Processes

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“…Cell culture dynamics, metabolism and product glycosylation have been modelled in the past using mechanistic models [ 56 , 57 , 58 ], statistical models [ 59 , 60 , 61 ], and hybrid models [ 61 , 62 ]. The application of CFD for hydrodynamic characterisation and scale-up and CRK for cell metabolism modelling has been extensively reviewed recently [ 63 , 64 , 65 , 66 ]. In this review, the focus is on the research articles wherein both the CFD and CRK modelling approaches have been integrated as this strategy has the potential to optimise the whole bioprocess rather than optimisation advances in just unit steps involved in bioprocessing.…”

Section: Introductionmentioning

confidence: 99%

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation

Singh,

Jiménez del Val,

Glassey

et al. 2024

Bioengineering

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Large-scale bioprocesses are increasing globally to cater to the larger market demands for biological products. As fermenter volumes increase, the efficiency of mixing decreases, and environmental gradients become more pronounced compared to smaller scales. Consequently, the cells experience gradients in process parameters, which in turn affects the efficiency and profitability of the process. Computational fluid dynamics (CFD) simulations are being widely embraced for their ability to simulate bioprocess performance, facilitate bioprocess upscaling, downsizing, and process optimisation. Recently, CFD approaches have been integrated with dynamic Cell reaction kinetic (CRK) modelling to generate valuable information about the cellular response to fluctuating hydrodynamic parameters inside large production processes. Such coupled approaches have the potential to facilitate informed decision-making in intelligent biomanufacturing, aligning with the principles of “Industry 4.0” concerning digitalisation and automation. In this review, we discuss the benefits of utilising integrated CFD-CRK models and the different approaches to integrating CFD-based bioreactor hydrodynamic models with cellular kinetic models. We also highlight the suitability of different coupling approaches for bioprocess modelling in the purview of associated computational loads.

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“…It has been used in the biopharmaceutical industry for years and has established itself as an important tool for process engineering characterization. As a result, CFD simulations are increasingly being used to complement classical process engineering investigations in the laboratory with spatially and temporally resolved results, or even replace them when laboratory investigations are not possible [25]. The use of digital twins in tissue engineering (TE) applications is of paramount importance to reduce the number of in vitro and in vivo tests.…”

Section: Introductionmentioning

confidence: 99%

Computational and Experimental Investigation of the Combined Effect of Various 3D Scaffolds and Bioreactor Stimulation on Human Cells’ Feedback

Kozaniti

Manara

Kostopoulos

et al. 2023

Applied Biosciences

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Computational methods were combined with an experimental setup in order to investigate the response of human umbilical cord stem cells to 3D electrospun and printed scaffolds, when dynamically stimulated in a bioreactor. Key parameters associated to bioreactor working conditions were computationally investigated using Comsol software to use the output for the planned experimental setup. Based on the theoretical observations, the influence of the inlet velocity, cell number, and exposure time in the bioreactor were analyzed and the in vitro parameters were adjusted accordingly. MSCs were seeded in different numbers in the 3D porous scaffolds and stimulated in the bioreactor (0.5 and 2 h duration, 3 and 6 mm/s inlet velocity). Polycaprolactone 3D electrospun, and polyurethane and polylactic acid 3D-printed scaffolds were fabricated and fibronectin-coated. The computational study predicted initial events in the process of cells deposition and attachment. Total protein, osteopontin, and osteocalcin levels in cells deposited in scaffolds were investigated; SEM and confocal imaging confirmed the biomarker analysis. MSCs proliferated well in PCL. Polyurethane enabled extremely rapid proliferation followed by differentiation, while PLA induced a moderate proliferation and parallel mineralization. The scaffolds stiffness has been found as the key enabling parameter decisive for cells feedback.

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Computational Fluid Dynamics for Advanced Characterisation of Bioreactors Used in the Biopharmaceutical Industry – Part I: Literature Review

Cited by 4 publications

References 157 publications

Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors

Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation

Computational and Experimental Investigation of the Combined Effect of Various 3D Scaffolds and Bioreactor Stimulation on Human Cells’ Feedback

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