通过使用第一个工业智能实验室框架进行深度学习驱动的机器人实验,创新细胞培养过程开发.
Shuting Xu1, Yanting Huang1, Xin Shen1
1Cell Culture Process Development (CCPD), WuXi Biologics, Shanghai, China.
Biotechnology progress
|June 21, 2025
概括
本研究介绍了一种人工智能驱动的机器人实验室框架,用于生物学过程开发. 它显著提高了细胞培养效率和蛋白质生产标位,加速了生物制造.
科学领域:
- 生物技术是生物技术.
- 工艺工程是过程工程.
- 人工智能的人工智能
背景情况:
- 传统的生物制品工艺开发是低效的,依赖于劳动密集型优化.
- 目前用于抗体和重组蛋白质生产的方法需要广泛的代细胞培养优化.
研究的目的:
- 开发一个自主实验室框架,工业智能实验室细胞培养框架 (ISLFCC),以增强细胞培养过程.
- 通过人工智能和机器人自动化加速生物制品开发和生物制造.
主要方法:
- 实现了ISLFCC,将深度学习 (只有解码器的变压器模型) 与机器人实验相结合.
- 利用物联网系统从生物反应器传输数据到人工智能模型并执行自动化操作.
- 采用人工智能来预测细胞状态并推最佳行动,如营养料和温度调整.
主要成果:
- 在单一批的三个细胞克隆中,达到26.8%的平均标位增加.
- 维持乳酸水平低于1g/L,没有晚期反弹.
- 在3L和15L生物反应堆中证明了增强的可复制性,数据准确性,适应性和可扩展性.
结论:
- ISLFCC框架为生物制造提供了一个变革性的,自主性的,数据驱动的方法.
- 这种人工智能驱动的方法与传统的经验方法相比,大大加快了生物学的发展.
- 代表了转向生物制药生产中自动化,高通量细胞培养的范式转变.
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