Mathematical Modelling to Define a New Design Rationale for Tissue-Engineered Peripheral Nerve Repair Constructs

数学建模定义组织工程周围神经修复结构的新设计原理

• 批准号: EP/N033493/1
• 负责人: Rebecca Shipley
• 金额: $ 12.84万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN033493%2F1
• 关键词: Mathematical; Modelling; Define; New; Design

Peripheral nerve injuries result from traumatic injury, surgery or repetitive compression, and their impact ranges from severe (leading to major loss of function or intractable neuropathic pain) to mild (some sensory and/or motor deficits affecting quality of life). The current clinical best practice for nerve gaps > 3 cm is to bridge the site of injury with a graft taken from the patient; however, this involves additional time, cost and damage to a healthy nerve, the amount of donor nerve is limited, and functional recovery of the main injury only occurs in ~50% of cases. For these reasons, research has focused on developing artificial nerve conduits to replace grafts, but to-date those available for clinical use can only bridge short (<3 cm) gaps and don't contain the living cells found in grafts. Stem cell technology provides a source of therapeutic cells for engineering living artificial nerve replacement tissue, but progress is limited due in part to a lack of consensus on the subtle interplay between the spatial arrangement of cells in engineered tissue and their survival outcome when implanted. Cells require a critical oxygen concentration to retain their function; under oxygen-deprivation, cells produce chemical cues (growth factors) to promote the growth of a blood network into the tissue, and this is an essential component of the repair process. A denser population of cells will induce greater oxygen deprivation and associated growth factors with higher potential to generate a blood supply; however, the increase in oxygen deprivation may also induce cell death, and therefore a sub-optimal construct. Resolving this sensitive balance purely experimentally would require an unrealistic, costly and ethically-questionable level of animal experimentation; the aim of this proposal is to develop a mathematical model of the tension between oxygenation, cell viability and growth of a blood supply, providing a rational design base for distributing cells and materials within nerve repair conduits. The above aim will be achieved through a carefully designed combination of mathematical modelling and experimentation. The mathematical work will be performed by the hired PDRA, whilst UCL Mechanical Engineering will fund a PhD student to perform the experimental work. The mathematical models will track, for example, the density of different cell populations, and the concentration field of oxygen and related growth factors in a nerve repair construct. Key biological relationships must be quantified for these models to have predictive capabilities; examples include the rate of oxygen uptake by a cell population, and the resulting proliferation rate of the cells. The interplay between modelling and experiment is a key feature of the proposal. The flow of information is a two-way process: the mathematical models will utilise experimentally-derived data, but will also inform the experimental work by highlighting the experiments that will produce the most meaningful data, and by predicting the cell distributions and chemical/ physical gradients to be tested. The resulting experimentally-parameterised mathematical model will predict the sensitive interplay between oxygenation, cellular viability and blood vessel growth, providing significant insight into the biology that would not be possible using an experimental approach in isolation. The mathematical model will inform spatial distributions of cells and materials in a construct, that promote cell survival and growth of a vascular supply. These construct designs will provide a platform to underpin generation of new repair devices in the future, and the modelling-experimental framework developed will be ripe for application to a host of repair scenarios in the cell therapy field.

周围神经损伤由创伤性损伤、手术或重复压迫引起，其影响范围从严重（导致功能严重丧失或顽固性神经性疼痛）到轻度（影响生活质量的一些感觉和/或运动缺陷）。目前临床上对于神经间隙> 3 cm的最佳实践是用取自患者的移植物桥接损伤部位;然而，这涉及额外的时间、成本和对健康神经的损伤，供体神经的量有限，并且主要损伤的功能恢复仅发生在约50%的病例中。由于这些原因，研究集中在开发人工神经导管来取代移植物，但迄今为止，那些可用于临床使用的人工神经导管只能桥接短（<3厘米）的间隙，并且不包含移植物中发现的活细胞。干细胞技术为工程化活的人工神经替代组织提供了治疗性细胞的来源，但进展有限，部分原因是缺乏对工程化组织中细胞的空间排列与植入后存活结果之间微妙相互作用的共识。细胞需要临界氧浓度来保持其功能;在缺氧情况下，细胞产生化学信号（生长因子）来促进血液网络向组织中的生长，这是修复过程的重要组成部分。更密集的细胞群将诱导更大的缺氧和具有更高潜力的相关生长因子以产生血液供应;然而，缺氧的增加也可能诱导细胞死亡，因此是次优构建体。纯粹通过实验解决这种敏感的平衡将需要不切实际的，昂贵的和道德上有问题的动物实验水平;该提案的目的是开发一个数学模型的氧合，细胞活力和血液供应的增长之间的紧张关系，提供一个合理的设计基础神经修复管道内的细胞和材料的分布。上述目标将通过精心设计的数学建模和实验相结合来实现。数学工作将由雇佣的PDRA进行，而UCL机械工程将资助一名博士生进行实验工作。例如，数学模型将跟踪不同细胞群的密度，以及神经修复构建体中氧和相关生长因子的浓度场。关键的生物学关系必须量化，这些模型才能具有预测能力;例如，细胞群体的氧摄取速率以及由此产生的细胞增殖速率。建模和实验之间的相互作用是该提案的一个主要特点。信息流是一个双向过程：数学模型将利用实验数据，但也将通过突出显示将产生最有意义数据的实验以及预测待测细胞分布和化学/物理梯度来为实验工作提供信息。由此产生的实验参数化数学模型将预测氧合，细胞活力和血管生长之间的敏感相互作用，提供对生物学的重要见解，这是孤立地使用实验方法不可能实现的。数学模型将告知构建体中细胞和材料的空间分布，其促进细胞存活和血管供应的生长。这些结构设计将提供一个平台，以支持未来新的修复设备的生成，并且所开发的建模实验框架将成熟，可应用于细胞治疗领域的许多修复场景。

项目成果

Combining in silico and in vitro models to inform cell seeding strategies in tissue engineering.

• DOI: 10.1098/rsif.2019.0801
• 发表时间: 2020-03-01
• 期刊: Journal of the Royal Society, Interface
• 作者: Coy, R;Al-Badri, G;Shipley, R J
• 通讯作者: Shipley, R J

An integrated theoretical-experimental approach to accelerate translational tissue engineering.

• DOI: 10.1002/term.2346
• 发表时间: 2018-01
• 期刊: Journal of tissue engineering and regenerative medicine
• 影响因子: 3.3
• 作者: Coy RH;Evans OR;Phillips JB;Shipley RJ
• 通讯作者: Shipley RJ

Developing an In Vitro Model to Screen Drugs for Nerve Regeneration.

• DOI: 10.1002/ar.23918
• 发表时间: 2018-10
• 期刊: Anatomical record (Hoboken, N.J. : 2007)
• 作者: Rayner MLD;Laranjeira S;Evans RE;Shipley RJ;Healy J;Phillips JB
• 通讯作者: Phillips JB

Vascularization Strategies for Peripheral Nerve Tissue Engineering.

• DOI: 10.1002/ar.23919
• 发表时间: 2018-10
• 期刊: Anatomical record (Hoboken, N.J. : 2007)
• 作者: Muangsanit P;Shipley RJ;Phillips JB
• 通讯作者: Phillips JB