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在CAR T细胞生产过程中对代谢状态的动态估计
N Suhas Jagannathan1, Wei-Xiang Sin2, Denise Bei Lin Teo2
1Critical Analytics for Manufacturing Personalized-Medicine (CAMP), Singapore-MIT Alliance for Research and Technology Centre (SMART), Singapore 138602, Singapore; Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore.
Cell reports methods
|February 12, 2026
概括
我们开发了一种实时建模工具,用于估计T细胞在体外扩张期间的代谢率. 这种方法有助于提高细胞治疗的一致性,通过将早期代谢数据与最终产品属性相关联,从而实现适应性过程控制.
科学领域:
- 生物技术是生物技术.
- 细胞生物学 细胞生物学
- 工艺工程是过程工程.
背景情况:
- 在细胞疗法中,T细胞的ex vivo扩张至关重要.
- 在扩张过程中监测细胞代谢是质量控制的关键.
- 目前的方法缺乏实时,每个细胞的新陈代谢率估计.
研究的目的:
- 介绍一种新的建模框架,用于实时估计ex vivo T 细胞培养中的每细胞代谢率.
- 为了验证模型的准确性和适用于不同类型的反应堆.
- 为了证明早期代谢特征与最终T细胞产品特征之间的相关性.
主要方法:
- 开发一个计算建模框架用于代谢率估计.
- 使用代谢试验验证,并将其分解为单个T细胞表型.
- 适用于以健康和患者衍生T细胞为基础的 perfusion 微生物反应器.
主要成果:
- 成功实时估计每个细胞的新陈代谢速率.
- 估计率与代谢测试的验证.
- 早期代谢率与T细胞生长,分化和枯竭之间有明显的相关性.
- 在 perfusion 基微生物反应器中应用的原理证明.
结论:
- 开发的建模框架可以准确地实时监测ex vivoT细胞的代谢率.
- 早期的代谢见解可以预测最终细胞产品的关键属性.
- 该工具支持自适应过程控制,以提高细胞治疗的一致性.
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