Current workflows in autologous cell therapy manufacturing are reliant on manual processes that are difficult to scale out to meet patient demands. High throughput bioreactor systems that enable multiple cultures to occur in parallel can address this need, but require good bioprocess monitoring workflows to produce good quality cell therapy products. Commercial sampling systems have thus been developed for better feedback control and monitoring capabilities. However, they are targeted towards large scale processes and often bioreactor specific, making them less robust for integration across different bioreactor scales and types, such as perfusion-capable microbioreactors which allows for greater process intensification. Here, an automated cell culture sampling system (Auto-CeSS) was developed to eliminate laborious manual sampling while minimizing sterility risks for cell therapy manufacturing processes. The system is aseptically integrated with a variety of bioreactors of different working volumes. This system can accurately and aseptically sample a minimum volume of 30 μL and can consistently perform periodic sampling of supernatant over a minimum interval of 15 min. We integrated Auto-CeSS with a 2 mL perfusion microbioreactor and a 8 mL gas-permeable well-plate for T cell culture, collecting 200 μL of supernatant samples daily for metabolite analysis. Comparison of the metabolic profiles of the samples collected via Auto-CeSS versus manual sampling revealed insignificant differences in metabolite levels, including glucose, lactate, glutamine, and glutamate. This report demonstrates the potential of Auto-CeSS as an at-line sampling platform in a real-time T cell production run to facilitate in-process culture monitoring.
Automated, aseptic sampling with small-volume capacity from microbioreactors for cell therapy process analysis.
阅读:14
作者:Chan Zhi Xian, Chelvam Shruthi Pandi, Sin Wei-Xiang, Teo Denise Bei Lin, Abdul Rahim Ahmad Amirul Bin, Wu Ying Ying, Liu Dan, Birnbaum Michael E, Yong Derrick, Ram Rajeev J
| 期刊: | Frontiers in Bioengineering and Biotechnology | 影响因子: | 4.800 |
| 时间: | 2025 | 起止号: | 2025 Jul 31; 13:1612648 |
| doi: | 10.3389/fbioe.2025.1612648 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
