Bisgaard Jonas, Muldbak Monica, Cornelissen Sjef, Tajsoleiman Tannaz, Huusom Jakob K, Rasmussen Tue, Gernaey Krist V
Freesense ApS, Copenhagen, Denmark.
Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark.
Comput Struct Biotechnol J. 2020 Oct 15;18:2908-2919. doi: 10.1016/j.csbj.2020.10.004. eCollection 2020.
Production-scale fermentation processes in industrial biotechnology experience gradients in process variables, such as dissolved gases, pH and substrate concentrations, which can potentially affect the production organism and therefore the yield and profitability of the processes. However, the extent of the heterogeneity is unclear, as it is currently a challenge at large scale to obtain representative measurements from different zones of the reactor volume. Computational fluid dynamics (CFD) models have proven to be a valuable tool for better understanding the environment inside bioreactors. Without detailed measurements to support the CFD predictions, the validity of CFD models is debatable. A promising technology to obtain such measurements from different zones in the bioreactors are flow-following sensor devices, whose development has recently benefitted from advancements in microelectronics and sensor technology. This paper presents the state of the art within flow-following sensor device technology and addresses how the technology can be used in large-scale bioreactors to improve the understanding of the process itself and to test the validity of detailed computational models of the bioreactors in the future.
工业生物技术中的大规模发酵过程会经历诸如溶解气体、pH值和底物浓度等过程变量的梯度变化，这些变化可能会对生产生物体产生潜在影响，进而影响过程的产量和盈利能力。然而，异质性的程度尚不清楚，因为目前在大规模情况下，从反应器不同区域获取代表性测量数据是一项挑战。计算流体动力学（CFD）模型已被证明是更好地理解生物反应器内部环境的宝贵工具。由于缺乏详细测量数据来支持CFD预测，CFD模型的有效性存在争议。一种从生物反应器不同区域获取此类测量数据的有前景的技术是随流传感器装置，其发展最近受益于微电子学和传感器技术的进步。本文介绍了随流传感器装置技术的现状，并探讨了该技术如何用于大规模生物反应器，以增进对过程本身的理解，并在未来测试生物反应器详细计算模型的有效性。
