整合多模式监控,以动态控制大型3D组织生物反应器
Laura Chastagnier1, Sarah Pragnere1,2, Yilbert Gimenez1,3
13d.FAB, CNRS, INSA, CPE-Lyon, UMR5246, ICBMS, Université Claude Bernard Lyon 1, Villeurbanne, France.
Scientific reports
|January 7, 2026
概括
这项研究提出了一个新的框架,用于实时监测生物反应器中的工程组织,整合多种分析方法来跟踪组织成熟和改善生物制造控制.
科学领域:
- 组织工程和再生医学
- 生物工艺工程 生物工艺工程
- 生物材料科学 生物材料科学
背景情况:
- 组织工程的临床转化需要在生物反应器中对大规模组织成熟的非侵入性监测.
- 现有的方法缺乏对现实世界生物制造环境的综合操作演示.
- perfusion生物反应器系统对于培养厘米尺度的工程组织至关重要.
研究的目的:
- 开发和验证一个模块化分析框架,用于对工程组织成熟的综合实时监测.
- 证明结合物理化学,代谢,形态和 perfusion 监测策略的可行性.
- 为了实现组织培养过程的自适应性,反驱动的控制.
主要方法:
- 为10厘米3的生物打印纤维细胞组织开发定制的 perfusion 生物反应器.
- 实时在线监测物理化学参数 (温度,pH,O2).
- 使用拉曼光谱测定乳酸量化的代谢评估.
- 通过7特斯拉MRI进行非破坏性形态跟踪,以获得几何准确性和重塑.
- 使用计算流体动力学 (CFD) 和MRI速度计进行 perfusion 映射.
主要成果:
- 双气体比例,整合,导数 (PID) 调节显著提高了氧气控制精度 (偏差为128%至22%).
- 拉曼光谱技术实现了乳酸分泌的0.103g L-1的预测误差.
- 7特斯拉MRI量化了87.6%的几何真实性,并揭示了内部组织重塑.
- CFD和MRI速度测量证实了工程组织中的异质 perfusion 模式.
结论:
- 综合分析框架使组织成熟的定量实时表征成为可能.
- 这种方法将传统的生物过程监测与组织生物制造工作流程相结合.
- 证明的方法为适应性,反控制的组织培养铺平了道路.
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