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Anand A, McCahill M, Thomas J, Sood A, Kinross J, Dasgupta A, Rajendran A. An in-silico analysis of hydrodynamics and gas mass transfer characteristics in scale-down models for mammalian cell cultures. J Biotechnol 2024; 388:96-106. [PMID: 38642816 DOI: 10.1016/j.jbiotec.2024.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/01/2024] [Accepted: 04/17/2024] [Indexed: 04/22/2024]
Abstract
Bioprocess scale-up and technology transfer can be challenging due to multiple variables that need to be optimized during process development from laboratory scale to commercial manufacturing. Cell cultures are highly sensitive to key factors during process transfer across scales, including geometric variability in bioreactors, shear stress from impeller and sparging activity, and nutrient gradients that occur due to increasing blend times. To improve the scale-up and scale-down of these processes, it is important to fully characterize bioreactors to better understand the differences that will occur within the culture environment, especially the hydrodynamic profiles that will vary in vessel designs across scales. In this study, a comprehensive hydrodynamic characterization of the Ambr® 250 mammalian single-use bioreactor was performed using time-accurate computational fluid dynamics simulations conducted with M-Star computational fluid dynamics software, which employs lattice-Boltzmann techniques to solve the Navier-Stokes transport equations at a mesoscopic scale. The single-phase and two-phase fluid properties within this small-scale vessel were analyzed in the context of agitation hydrodynamics and mass transfer (both within the bulk fluid and the free surface) to effectively characterize and understand the differences that scale-down models possess when compared to their large-scale counterparts. The model results validate the use of computational fluid dynamics as an in-silico tool to characterize bioreactor hydrodynamics and additionally identify important free-surface transfer mechanics that need to be considered during the qualification of a scale-down model in the development of mammalian bioprocesses.
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Affiliation(s)
- Alaina Anand
- Bioprocess Research and Development, Pfizer, Andover, MA 01810, USA
| | - Madelynn McCahill
- Manufacturing Sciences and Technology, Global Technology and Engineering, Pfizer, Andover, MA 01810, USA; Manufacturing Intelligence, Global Technology and Engineering, Pfizer, Andover, MA, USA
| | - John Thomas
- M-Star Simulations, 11000 Baltimore National Pike, Ellicott City, MD 21042, USA
| | - Aishwarya Sood
- Manufacturing Sciences and Technology, Global Technology and Engineering, Pfizer, Andover, MA 01810, USA
| | - Jonathan Kinross
- Manufacturing Sciences and Technology, Global Technology and Engineering, Pfizer, Andover, MA 01810, USA
| | - Aparajita Dasgupta
- Manufacturing Sciences and Technology, Global Technology and Engineering, Pfizer, Andover, MA 01810, USA.
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Oliveira CL, Pace Z, Thomas JA, DeVincentis B, Sirasitthichoke C, Egan S, Lee J. CFD-based bioreactor model with proportional-integral-derivative controller functionality for dissolved oxygen and pH. Biotechnol Bioeng 2024; 121:655-669. [PMID: 38031493 DOI: 10.1002/bit.28598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/26/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023]
Abstract
A physics-based model for predicting cell culture fluid properties inside a stirred tank bioreactor with embedded PID controller logic is presented. The model evokes a time-accurate solution to the fluid velocity field and overall volumetric mass transfer coefficient, as well as the ongoing effects of interfacial mass transfer, species mixing, and aqueous chemical reactions. The modeled system also includes a direct coupling between process variables and system control variables via embedded controller logic. Satisfactory agreement is realized between the model prediction and measured bioreactor data in terms of the steady-state operating conditions and the response to setpoint changes. Simulation runtimes are suitable for industrial research and design timescales.
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Affiliation(s)
- Christopher L Oliveira
- Bristol Myers Squibb Company, Global Product Development and Supply, Devens, Massachusetts, USA
| | - Zoe Pace
- Bristol Myers Squibb Company, Global Product Development and Supply, Devens, Massachusetts, USA
- Biomedical Engineering Department, Worcester Polytechnic Institute, Worcester, Massachusetts, USA
| | | | | | | | - Susan Egan
- Bristol Myers Squibb Company, Global Product Development and Supply, Devens, Massachusetts, USA
| | - Jongchan Lee
- Bristol Myers Squibb Company, Global Product Development and Supply, Devens, Massachusetts, USA
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Thomas JA, DeVincentis B, Hanspal N, Kehn RO. Predicting gas-liquid mass transfer rates in reactors using a bubble parcel model. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.118183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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