Modelling-informed cell-seeded nerve repair construct designs for treating peripheral nerve injuries

Millions of people worldwide are affected by peripheral nerve injuries (PNI), involving billions of dollars in healthcare costs. Common outcomes for patients include paralysis and loss of sensation, often leading to lifelong pain and disability. Engineered Neural Tissue (EngNT) is being developed as an alternative to the current treatments for large-gap PNIs that show underwhelming functional recovery in many cases. EngNT repair constructs are composed of a stabilised hydrogel cylinder, surrounded by a sheath of material, to mimic the properties of nerve tissue. The technology also enables the spatial seeding of therapeutic cells in the hydrogel to promote nerve regeneration. The identification of mechanisms leading to maximal nerve regeneration and to functional recovery is a central challenge in the design of EngNT repair constructs. Using in vivo experiments in isolation is costly and time-consuming, offering a limited insight on the mechanisms underlying the performance of a given repair construct. To bridge this gap, we derive a cell-solute model and apply it to the case of EngNT repair constructs seeded with therapeutic cells which produce vascular endothelial growth factor (VEGF) under low oxygen conditions to promote vascularisation in the construct. The model comprises a set of coupled non-linear diffusion-reaction equations describing the evolving cell population along with its interactions with oxygen and VEGF fields during the first 24h after transplant into the nerve injury site. This model allows us to evaluate a wide range of repair construct designs (e.g. cell-seeding strategy, sheath material, culture conditions), the idea being that designs performing well over a short timescale could be shortlisted for in vivo trials. In particular, our results suggest that seeding cells beyond a certain density threshold is detrimental regardless of the situation considered, opening new avenues for future nerve tissue engineering.
Author summary Mathematical models are increasingly gaining traction in biomedical sciences in general and in peripheral nerve repair in particular. These models can both help to unveil mechanisms underlying nerve regeneration post-injury and inform the design of new repair strategies, while continuously being improved through experiments and clinical data. In particular, cell-solute models provide flexible, computationally-efficient frameworks that enable access to spatio-temporal information difficult to reach in vivo in nerve repair scenarios. In this work, we derive such a model and apply it to the case of Engineered Neural Tissue repair constructs after their transplant into the nerve injury site. One key feature of such repair constructs is the spatial seeding of therapeutic cells capable of producing signalling molecules that promote nerve regeneration. We simulate the activity of such cells and evaluate, after 24h, cell survival and signalling molecule output for a range of nerve repair construct designs. The underlying hypothesis is that designs performing well at such short timescales could be shortlisted for in vivo trials, the latter being costly and time-consuming. Our results suggest that seeding cells beyond a certain density threshold is detrimental regardless of the situation considered, opening new avenues for future nerve repair construct design.