Today’s biomanufacturing processes are still operated based on experience, and thus can hardly cope with increasing bioprocess complexity. Recently, there is a growing interest in industrial applications of the digital twins (DT) which integrate physical and virtual systems via real-time data monitoring, thus enabling their interactive communications for the enhanced operational efficiency towards advanced biomanufacturing. We suggest that bioprocess DT of cell cultures can be developed by incorporating in-line monitoring, advanced data analytics with machine and deep learning, and mechanistic models representing the mammalian cells and bioreactor for virtually mirroring their behaviors under adjustable process conditions. In this review, we summarize and highlight recent advances in the key components within bioprocess DT platform and discuss the current challenges with future research direction.

当今的生物制造工艺仍然基于经验进行操作，因此难以应对日益增加的生物工艺复杂性。最近，人们对数字孪生 (DT) 的工业应用越来越感兴趣，它通过实时数据监控集成物理和虚拟系统，从而实现它们的交互式通信，以提高先进生物制造的运营效率。我们建议细胞培养的生物过程 DT 可以通过结合在线监测、高级数据分析与机器和深度学习以及代表哺乳动物细胞和生物反应器的机械模型来开发，以便在可调节的过程条件下虚拟地反映它们的行为。在这次审查中，