Development of a bioartificial nerve graft. I. Design based on a reaction-diffusion model

Area of Science:

• Biomaterials Science
• Tissue Engineering
• Computational Biology

Background:

• Bioartificial nerve grafts (BNGs) utilize porous polymer conduits seeded with Schwann cells to promote nerve regeneration.
• Efficient transport of nutrients and nerve growth factors is crucial for successful nerve repair within BNGs.
• Optimizing BNG design requires understanding the interplay between conduit properties and biological factors.

Purpose of the Study:

• To develop a reaction-diffusion model for simulating mass transport within BNGs.
• To predict optimal bioartificial nerve graft parameters for maximizing axon extension rate.
• To ensure adequate nutrient supply, particularly oxygen, to neurons during regeneration.

Main Methods:

• A simple reaction-diffusion model was employed.
• The model simulates the transport of nutrients and nerve growth factor (NGF).
• It incorporates parameters such as wall thickness, porosity, and Schwann cell seeding density.

Main Results:

• Model predicts a sixteen-fold increase in NGF by reducing porosity from 95% to 55%, with a trade-off in oxygen concentration.
• Higher porosities benefit from increased wall thickness and Schwann cell seeding density to raise NGF levels.
• The model provides insights into optimizing conduit design for nerve regeneration.

Conclusions:

• The developed model serves as a valuable tool for evaluating bioartificial nerve graft designs.
• It aids in optimizing parameters to enhance nerve regeneration while maintaining essential nutrient supply.
• In silico evaluation can guide future in vivo experimental studies for improved BNG development.