In silico Approaches for the Identification of Optimal Culture Condition for Tissue Engineered Bone Substitutes

Abstract

Tissue engineered bone grafts are among the most promising approaches to heal large bone defects. An in vitro culture phase prior to transplantation provides the opportunity to optimize the graft properties. In our study we developed computational models for the investigation of the deformation, perfusion and revascularization of a porous β-tricalcium phosphate (β-TCP) scaffold seeded with human bone marrow derived mesenchymal stem cells (MSCs). The deformation model allows predicting the resulting forces in the β-TCP scaffold due to different external loadings. In addition to pressure related forces, fluid convection within the scaffold also exerts shear stress onto the cells. However, perfusion is necessary for the supply of the cells with nutrients such as glucose. To find an optimal ratio between shear stress and nutrients supply, we develop fluidic models for the β-TCP scaffold. Furthermore to the scaffold specifications, also the cellular glucose consumption of osteogenic differentiated and undifferentiated MSCs was integrated in the computational model. Beyond the in vitro culture phase, bone grafts have to be supplied by the host ’ s vascular system. Therefore angiogenesis has to be induced, e.g. by preloading the graft with pro angiogenic factors such as VEGF-A. A stochastic model, based on the Fokker-Planck equation was developed to investigate the impact of a given cytokine gradient onto the endothelial cell migration. The stochastic model was parameterized by data derived from live cell imaging studies.