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Computational fluid dynamics based digital twins of fixed bed bioreactors validate scaling principles for recombinant adeno‐associated virus gene therapy manufacturing
Biotechnology and Bioengineering ( IF 3.8 ) Pub Date : 2024-05-06 , DOI: 10.1002/bit.28727
Michael Hill 1, 2 , Colten White 1 , Shaoying Wang 1 , John Thomas 3 , Brian DeVincentis 3 , Nripen Singh 1
Affiliation  

Gene therapy using recombinant adeno‐associated virus (rAAV) as delivery vehicles has garnered much interest in recent years. There are still significant gaps in our fundamental understanding of the manufacturing processes to deliver sufficient products. Manufacturing efforts of rAAV using HEK293 cells have commonly relied on fixed bed falling film bioreactors like the iCELLis®. We used computational fluid dynamics (CFD) to validate the operating conditions required for a predictive iCELLis® 500 scale‐down model. The small‐scale and at‐scale systems have different flow paths causing validation of the corresponding agitation rates required to achieve the same linear flow through the fixed bed across scales to be non‐trivial. Therefore, we used CFD to predict the theoretical scaling relationship. In addition, CFD could predict kLa differences between the two systems and the operating conditions required to match kLa between scales. We also confirmed that the location of DO control must be the same in both systems to achieve proper scaling. Experimental runs confirming the validity of the novel scale‐down model showed that based on the modifications to the iCELLis® Nano system, we achieved similar DO, key metabolite, pH, and GC titer trends in both systems.

中文翻译:

基于计算流体动力学的固定床生物反应器数字孪生验证了重组腺相关病毒基因治疗制造的缩放原理

近年来,使用重组腺相关病毒(rAAV)作为递送载体的基因治疗引起了广泛关注。我们对提供足够产品的制造流程的基本理解仍然存在重大差距。使用 HEK293 细胞生产 rAAV 通常依赖于 iCELLis® 等固定床降膜生物反应器。我们使用计算流体动力学 (CFD) 来验证预测 iCELLis® 500 缩小模型所需的操作条件。小规模和大规模系统具有不同的流动路径,导致验证跨规模固定床实现相同线性流动所需的相应搅拌速率并非易事。因此,我们使用CFD来预测理论缩放关系。此外,CFD 可以预测两个系统之间的 kLa 差异以及在秤之间匹配 kLa 所需的操作条件。我们还确认两个系统中 DO 控制的位置必须相同,才能实现适当的缩放。实验运行证实了新型缩小模型的有效性,表明基于对 iCELLis® Nano 系统的修改,我们在两个系统中实现了相似的 DO、关键代谢物、pH 和 GC 滴度趋势。
更新日期:2024-05-06
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