Fattahi Ehsan, Taheri Shahed, Schilling Arndt F, Becker Thomas, Pörtner Ralf
Chair of Brewing and Beverage Technology TUM School of Life Sciences Technische Universität München Freising Germany.
Department of Trauma Surgery Orthopaedics and Plastic Surgery University Medical Center Göttingen Göttingen Germany.
Eng Life Sci. 2022 Feb 23;22(11):681-698. doi: 10.1002/elsc.202100128. eCollection 2022 Nov.
Techniques for tissue culture have seen significant advances during the last decades and novel 3D cell culture systems have become available. To control their high complexity, experimental techniques and their Digital Twins (modelling and computational tools) are combined to link different variables to process conditions and critical process parameters. This allows a rapid evaluation of the expected product quality. However, the use of mathematical simulation and Digital Twins is critically dependent on the precise description of the problem and correct input parameters. Errors here can lead to dramatically wrong conclusions. The intention of this review is to provide an overview of the state-of-the-art and remaining challenges with respect to generating input values for computational analysis of mass and momentum transport processes within tissue cultures. It gives an overview on relevant aspects of transport processes in tissue cultures as well as modelling and computational tools to tackle these problems. Further focus is on techniques used for the determination of cell-specific parameters and characterization of culture systems, including sensors for on-line determination of relevant parameters. In conclusion, tissue culture techniques are well-established, and modelling tools are technically mature. New sensor technologies are on the way, especially for organ chips. The greatest remaining challenge seems to be the proper addressing and handling of input parameters required for mathematical models. Following Good Modelling Practice approaches when setting up and validating computational models is, therefore, essential to get to better estimations of the interesting complex processes inside organotypic tissue cultures in the future.
在过去几十年中,组织培养技术取得了显著进展,新型三维细胞培养系统已问世。为了控制其高度复杂性,将实验技术及其数字孪生体(建模和计算工具)相结合,以将不同变量与工艺条件和关键工艺参数联系起来。这使得能够快速评估预期的产品质量。然而,数学模拟和数字孪生体的使用严重依赖于对问题的精确描述和正确的输入参数。这里的错误可能导致极其错误的结论。本综述的目的是概述在为组织培养中质量和动量传输过程的计算分析生成输入值方面的最新技术水平和剩余挑战。它概述了组织培养中传输过程的相关方面以及解决这些问题的建模和计算工具。进一步关注的是用于确定细胞特异性参数和表征培养系统的技术,包括用于在线确定相关参数的传感器。总之,组织培养技术已经成熟,建模工具在技术上也已成熟。新的传感器技术正在涌现,特别是用于器官芯片的技术。最大的剩余挑战似乎是正确处理数学模型所需的输入参数。因此,在建立和验证计算模型时遵循良好建模实践方法对于未来更好地估计器官型组织培养中有趣的复杂过程至关重要。