Aurélie Carlier

TL;DR: The use of computational models to simulate the CaP-driven osteogenesis is introduced as part of a bone tissue engineering strategy in order to facilitate the understanding of cell-material interactions and to gain further insight into the design and optimization ofCaP-based bone reparative units.

TL;DR: It is shown that obstruction of vascular invasion during bone healing favours chondrogenic over osteogenic differentiation of skeletal progenitor cells, driven by a decreased availability of extracellular lipids.

TL;DR: Machine learning is used to successfully build a model that correlates cell attachment and phenotype with a selection of descriptors, illustrating that materials can potentially be designed to modulate inflammatory responses for future applications in the fight against foreign body rejection of medical devices.

TL;DR: A novel multiscale model of osteogenesis and sprouting angiogenesis, incorporating lateral inhibition of endothelial cells (further denoted MOSAIC model) through Dll4-Notch1 signaling, and applies it to fracture healing is presented, demonstrating enhanced capabilities for investigating the influence of molecular mechanisms onAngiogenesis and its relation to bone formation in a more mechanistic way and across different time and spatial scales.

TL;DR: High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials as mentioned in this paper.