Centre for Nerve Engineering, University College London, WC1E 6BT London, UK.
Department of Mechanical Engineering, University College London, WC1E 6BT London, UK.
J R Soc Interface. 2023 Sep;20(206):20230258. doi: 10.1098/rsif.2023.0258. Epub 2023 Sep 6.
Cellular engineered neural tissues have significant potential to improve peripheral nerve repair strategies. Traditional approaches depend on quantifying tissue behaviours using experiments in isolation, presenting a challenge for an overarching framework for tissue design. By comparison, mathematical cell-solute models benchmarked against experimental data enable computational experiments to be performed to test the role of biological/biophysical mechanisms, as well as to explore the impact of different design scenarios and thus accelerate the development of new treatment strategies. Such models generally consist of a set of continuous, coupled, partial differential equations relying on a number of parameters and functional forms. They necessitate dedicated experiments to be informed, which are seldom available and often involve small datasets with limited spatio-temporal resolution, generating uncertainties. We address this issue and propose a pipeline based on Bayesian inference enabling the derivation of experimentally informed cell-solute models describing therapeutic cell behaviour in nerve tissue engineering. We apply our pipeline to three relevant cell types and obtain models that can readily be used to simulate nerve repair scenarios and quantitatively compare therapeutic cells. Beyond parameter estimation, the proposed pipeline enables model selection as well as experiment utility quantification, aimed at improving both model formulation and experimental design.
细胞工程化神经组织在改善周围神经修复策略方面具有巨大的潜力。传统方法依赖于通过独立的实验来量化组织行为，这对于组织设计的总体框架来说是一个挑战。相比之下，经过实验数据基准测试的数学细胞溶质模型可以进行计算实验，以测试生物/生物物理机制的作用，以及探索不同设计方案的影响，从而加速新治疗策略的开发。这些模型通常由一组连续的、耦合的偏微分方程组成，依赖于许多参数和函数形式。它们需要有专门的实验来提供信息，但这些实验很少且往往涉及具有有限时空分辨率的小数据集，从而产生不确定性。我们解决了这个问题，并提出了一个基于贝叶斯推理的管道，该管道能够推导出描述神经组织工程中治疗细胞行为的基于实验的细胞溶质模型。我们将我们的管道应用于三种相关的细胞类型，并获得了可以方便地用于模拟神经修复场景和定量比较治疗细胞的模型。除了参数估计之外，所提出的管道还能够进行模型选择和实验效用量化，旨在改进模型制定和实验设计。
