Scale-Up analysis for a CHO cell culture process in large-scale bioreactors
Process Sciences, Biologics Manufacturing and Process Development, Worldwide Medicines Group, Bristol-Myers Squibb Company, Syracuse, NY 13221-4755, USA.Biotechnology and Bioengineering (Impact Factor: 4.13). 07/2009; 103(4):733-46. DOI: 10.1002/bit.22287
Bioprocess scale-up is a fundamental component of process development in the biotechnology industry. When scaling up a mammalian cell culture process, it is important to consider factors such as mixing time, oxygen transfer, and carbon dioxide removal. In this study, cell-free mixing studies were performed in production scale 5,000-L bioreactors to evaluate scale-up issues. Using the current bioreactor configuration, the 5,000-L bioreactor had a lower oxygen transfer coefficient, longer mixing time, and lower carbon dioxide removal rate than that was observed in bench scale 5- and 20-L bioreactors. The oxygen transfer threshold analysis indicates that the current 5,000-L configuration can only support a maximum viable cell density of 7 x 10(6) cells mL(-1). Moreover, experiments using a dual probe technique demonstrated that pH and dissolved oxygen gradients may exist in 5,000-L bioreactors using the current configuration. Empirical equations were developed to predict mixing time, oxygen transfer coefficient, and carbon dioxide removal rate under different mixing-related engineering parameters in the 5,000-L bioreactors. These equations indicate that increasing bottom air sparging rate is more efficient than increasing power input in improving oxygen transfer and carbon dioxide removal. Furthermore, as the liquid volume increases in a production bioreactor operated in fed-batch mode, bulk mixing becomes a challenge. The mixing studies suggest that the engineering parameters related to bulk mixing and carbon dioxide removal in the 5,000-L bioreactors may need optimizing to mitigate the risk of different performance upon process scale-up.
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- "Besides the hydrodynamic stress magnitude , the exposure period is another parameter which has to be properly controlled (Sieck et al., 2013). It can be estimated from the mixing times (t mix ) which are reported, for a 5000 L bioreactor in the order of 1–2 min, depending on the conditions (Xing et al., 2009). The measured t mix of an in house 5000 L bioreactor used for both cells at manufacturing scale was equal to 45 s, at culture operating conditions. "
ABSTRACT: Application of quality by design (QbD) requires identification of the maximum operating range for parameters affecting the cell culture process. These include hydrodynamic stress, mass transfer or gradients in dissolved oxygen and pH. Since most of these are affected by the impeller design and speed, the main goal of this work was to identify a maximum operating range for hydrodynamic stress, where no variation of cell growth, productivity and product quality can be ensured. Two scale-down models were developed operating under laminar and turbulent condition, generating repetitive oscillating hydrodynamic stress with maximum stress values ranging from 0.4 to 420Pa, to compare the effect of the different flow regimes on the cells behavior. Two manufacturing cell lines (CHO and Sp2/0) used for the synthesis of therapeutic proteins were employed in this study. For both cell lines multiple process outputs were used to determine the threshold values of hydrodynamic stress, such as cell growth, morphology, metabolism and productivity. They were found to be different in between the cell lines with values equal to 32.4±4.4Pa and 25.2±2.4 Pa for CHO and Sp2/0, respectively. Below the measured thresholds both cell lines do not show any appreciable effect of the hydrodynamic stress on any critical quality attribute, while above, cells responded negatively to the elevated stress. To confirm the applicability of the proposed method, the obtained results were compared with data generated from classical small-scale reactors with a working volume of 3L. Copyright © 2014. Published by Elsevier B.V.Journal of Biotechnology 12/2014; 194. DOI:10.1016/j.jbiotec.2014.12.003 · 2.87 Impact Factor
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- "Among the cell lines available for mAb production are myeloma, hybridoma, and Chinese hamster ovary (CHO) cell lines [3,4]. The use of CHO cells in large-scale production is common [3,5-7] because of their ability to express high recombinant protein levels [8,9], grow to high cell densities [10-13], and to grow in serum-free suspension culture [6,14-16]. CHO cells are also suitable for use with expression systems, such as dihydrofolate reductase (DHFR) and glutamine synthetase (GS) [17-19]. "
ABSTRACT: High recombinant protein productivity in mammalian cell lines is often associated with phenotypic changes in protein content, energy metabolism, and cell growth, but the key determinants that regulate productivity are still not clearly understood. The mammalian target of rapamycin (mTOR) signalling pathway has emerged as a central regulator for many cellular processes including cell growth, apoptosis, metabolism, and protein synthesis. This role of this pathway changes in response to diverse environmental cues and allows the upstream proteins that respond directly to extracellular signals (such as nutrient availability, energy status, and physical stresses) to communicate with downstream effectors which, in turn, regulate various essential cellular processes. In this study, we have performed a transcriptomic analysis using a pathway-focused polymerase chain reaction (PCR) array to compare the expression of 84 target genes related to the mTOR signalling in two recombinant CHO cell lines with a 17.4-fold difference in specific monoclonal antibody productivity (qp). Eight differentially expressed genes that exhibited more than a 1.5-fold change were identified. Pik3cd (encoding the Class 1A catalytic subunit of phosphatidylinositol 3-kinase [PI3K]) was the most differentially expressed gene having a 71.3-fold higher level of expression in the high producer cell line than in the low producer. The difference in the gene's transcription levels was confirmed at the protein level by examining expression of p110delta. Expression of p110delta correlated with specific productivity (qp) across six different CHO cell lines, with a range of expression levels from 3 to 51 pg/cell/day, suggesting that p110delta may be a key factor in regulating productivity in recombinant cell lines.BMC Biotechnology 02/2014; 14(1):15. DOI:10.1186/1472-6750-14-15 · 2.03 Impact Factor
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- "A practical explicit formula is (4) where H 2 O is the concentration of water in the liquid phase, He C Henry's constant for CO 2 , p the actual total pressure and y C the molar fraction of CO 2 in the gas phase. In literature (e.g., Xing et al. ), y C is most often assumed to be the carbon dioxide concentration in the air pressed into the sparger and that is the very problem. Due to mass transfer across the bubble interfacial area, A B , changes in the amount n C of CO 2 within a single representative gas bubble along its path in the continuous liquid phase can be described by the simple ordinary differential equation in n C (5) which can easily be derived from Eq. (1). "
ABSTRACT: Most discussions about stirred tank bioreactors for cell cultures focus on liquid-phase motions and neglect the importance of the gas phase for mixing, power input and especially CO(2) stripping. Particularly in large production reactors, CO(2) removal from the culture is known to be a major problem. Here, we show that stripping is mainly affected by the change of the gas composition during the movement of the gas phase through the bioreactor from the sparger system towards the headspace. A mathematical model for CO(2)-stripping and O(2)-mass transfer is presented taking gas-residence times into account. The gas phase is not moving through the reactor in form of a plug flow as often assumed. The model is validated by measurement data. Further measurement results are presented that show how the gas is partly recirculated by the impellers, thus increasing the gas-residence time. The gas-residence times can be measured easily with stimulus-response techniques. The results offer further insights on the gas-residence time distributions in stirred tank reactors.Biotechnology Journal 12/2011; 6(12):1547-56. DOI:10.1002/biot.201100153 · 3.49 Impact Factor
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