Computational nanomedicine for mechanistic elucidation of bilayer nanoparticle-mediated release for tissue engineering

Aim: Temporal control of growth-factor release from nanoparticles is essential to many tissue engineering applications, yet remains a challenge due to its complicated behavior. The interplay between nanoparticle characteristics and release mechanisms can be captured using computational models. This study aims to develop two novel models to represent the release of bilayer nanoparticles. Materials & methods: Bilayer nanoparticles were prepared and characterized experimentally. `Local volume averaging' and `Geno-Mechanistic' models were developed and validated with experiments, and then used to identify critical release parameters and elucidate the release mechanisms. Results: Models presented an agreement with experimental data and successfully estimated transport/degradation parameters, which were closely associated with nanoparticle polymer mass ratio and crystallinity. Models suggested that despite relatively rapid core degradation, shell predominantly controlled overall release patterns. Conclusion: The developed models and computational frameworks offer a great potential for optimizing/tuning bilayer polymeric nanoparticles for tissue engineering applications.