Regenerative medicine (RM) holds the promise to cure many of what are now chronic patients, restoring health rather than protracting decline, bettering the lives of millions and at the same time preventing lifelong, expensive care processes: cure instead of care. The scientific community has made large steps in this direction over the past decade, however our understanding of the fundamentals of cell, tissue and organ regeneration and of how to stimulate and guide this with intelligent biomaterials in the human body is still in its infancy. Materials properties such as elasticity, topography, hydrophobicity, and porosity have all been shown to influence cell fate, and the introduction of high-throughput combinatorial approaches is expediting research. However, in order to improve the design of synthetic biomaterials, it is crucial to understand the physiological cell-biomaterial interactions and how these influence the tissue remodeling process. This research project aims to use in silico models to simulate physiological and fibrotic cell-ECM interactions, including dynamic tissue remodeling through ECM deposition and alignment, to improve our fundamental understanding thereof and use the obtained knowledge to design improved synthetic matrices.
Project description:
- Computational modeling of tissue remodeling to inform the design of synthetic matrices
- Multiscale modeling: coupling ABM to FEM to investigate the role of dynamic tissue compositions and alignment
- Parameter optimization and sensitivity analysis
- Analysis and integration of various in vitro/in vivo data for model calibration
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