Sarkar Jayati, Shekhawat Lalita Kanwar, Loomba Varun, Rathore Anurag S
Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India.
Biotechnol Prog. 2016 May;32(3):613-28. doi: 10.1002/btpr.2242. Epub 2016 Feb 29.
Mixing in bioreactors is known to be crucial for achieving efficient mass and heat transfer, both of which thereby impact not only growth of cells but also product quality. In a typical bioreactor, the rate of transport of oxygen from air is the limiting factor. While higher impeller speeds can enhance mixing, they can also cause severe cell damage. Hence, it is crucial to understand the hydrodynamics in a bioreactor to achieve optimal performance. This article presents a novel approach involving use of computational fluid dynamics (CFD) to model the hydrodynamics of an aerated stirred bioreactor for production of a monoclonal antibody therapeutic via mammalian cell culture. This is achieved by estimating the volume averaged mass transfer coefficient (kL a) under varying conditions of the process parameters. The process parameters that have been examined include the impeller rotational speed and the flow rate of the incoming gas through the sparger inlet. To undermine the two-phase flow and turbulence, an Eulerian-Eulerian multiphase model and k-ε turbulence model have been used, respectively. These have further been coupled with population balance model to incorporate the various interphase interactions that lead to coalescence and breakage of bubbles. We have successfully demonstrated the utility of CFD as a tool to predict size distribution of bubbles as a function of process parameters and an efficient approach for obtaining optimized mixing conditions in the reactor. The proposed approach is significantly time and resource efficient when compared to the hit and trial, all experimental approach that is presently used. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:613-628, 2016.
众所周知，生物反应器中的混合对于实现高效的质量和热传递至关重要，而这两者不仅会影响细胞生长，还会影响产品质量。在典型的生物反应器中，氧气从空气中的传输速率是限制因素。虽然较高的叶轮转速可以增强混合，但也可能导致严重的细胞损伤。因此，了解生物反应器中的流体动力学对于实现最佳性能至关重要。本文提出了一种新颖的方法，即使用计算流体动力学（CFD）对通过哺乳动物细胞培养生产单克隆抗体治疗药物的曝气搅拌生物反应器的流体动力学进行建模。这是通过在不同的工艺参数条件下估算体积平均传质系数（kL a）来实现的。已研究的工艺参数包括叶轮转速和通过气体分布器入口进入的气体流速。为了处理两相流和湍流问题，分别使用了欧拉-欧拉多相模型和k-ε湍流模型。这些模型进一步与群体平衡模型相结合，以纳入导致气泡聚并和破裂的各种相间相互作用。我们已经成功地证明了CFD作为预测气泡尺寸分布与工艺参数函数关系的工具的实用性，以及在反应器中获得优化混合条件的有效方法。与目前使用的反复试验的全实验方法相比，所提出的方法在时间和资源方面具有显著的效率。©2016美国化学工程师学会生物技术进展，32:613 - 628，2016。
