[en] In biomaterial-based bone tissue engineering, optimizing scaffold structure and composition
remains an active field of research. Additive manufacturing has enabled the production of
custom designs in a variety of materials. This study aims to improve the design of calcium-phosphatebased
additively manufactured scaffolds, the material of choice in oral bone regeneration, by using a
combination of in silico and in vitro tools. Computer models are increasingly used to assist in design
optimization by providing a rational way of merging different requirements into a single design.
The starting point for this study was an in-house developed in silico model describing the in vitro
formation of neotissue, i.e., cells and the extracellular matrix they produced. The level set method was
applied to simulate the interface between the neotissue and the void space inside the scaffold pores.
In order to calibrate the model, a custom disk-shaped scaffold was produced with prismatic canals of
different geometries (circle, hexagon, square, triangle) and inner diameters (0.5 mm, 0.7 mm, 1 mm,
2 mm). The disks were produced with three biomaterials (hydroxyapatite, tricalcium phosphate,
and a blend of both). After seeding with skeletal progenitor cells and a cell culture for up to 21 days,
the extent of neotissue growth in the disks’ canals was analyzed using fluorescence microscopy.
The results clearly demonstrated that in the presence of calcium-phosphate-based materials, the
curvature-based growth principle was maintained. Bayesian optimization was used to determine
the model parameters for the different biomaterials used. Subsequently, the calibrated model was
used to predict neotissue growth in a 3D gyroid structure. The predicted results were in line with
the experimentally obtained ones, demonstrating the potential of the calibrated model to be used
as a tool in the design and optimization of 3D-printed calcium-phosphate-based biomaterials for
Funding text :
This research was funded by the Walloon Region (SPW Recherche) through the BioWin
project BIOPTOS (ID: 7560) and the Win2Wal project B2Bone (2210023), the Fund for Scientific
Research Belgium FNRS-FRFC (project ID: T.0256.16), the Interreg VA Flanders—The Netherlands
project Prosperos (grant no.: 2014TC16RFCB046), and the European Union’s Horizon 2020 research
and innovation program via the European Research Council (ERC CoG INSITE 772418). The APC
was funded by the Walloon Region (SPW Recherche) through the Win2Wal project B2Bone (2210023).