In Silico Biology of Bone Regeneration Inside Calcium Phosphate Scaffolds - Tissue Engineering: Computer Modeling, Biofabrication and Cell Behavior - page 41

cells further down the osteoblastic lineage. A least-square fitting through the experi-
mental data determined the parameters that characterize the influence of calcium on
the proliferation of MSCs and osteoblasts.
Another example of this challenge in experimental research is the determination
of the dissolution rate of CaP scaffolds. As shown by Carlier et al. [ 11 ], this prop-
erty has an important effect on the final amount of bone formation and should as
such be thoroughly characterized. However, the degradation rate is influenced by
many scaffold characteristics (e.g. micro- and macrostructure, the material compo-
sition, specific surface area) and testing conditions (e.g. temperature, composition
of dissolution medium, pH, specific surface area to medium ratio). Currently dis-
solution tests still lack standardization [ 22 ] and often the (CaP) scaffolds are not
completely characterized, making it very difficult to compare the results of different
studies found in literature. Impens et al. [ 22 ] show for example that perfusion tests
result in a higher dissolution rate when compared to bath shaking tests due to the
easier entrance of the fluid flow inside these scaffold. Moreover, these in vitro tests
do not take the influence of protein adsorption or osteoclastic activity after implan-
tation into account. From the above it is clear that there is still a long way to go and
that specific experiments should be designed that resemble the in vivo conditions as
close as possible.
3.3 ... and Back
The multidisciplinary problem of optimizing scaffold architecture and seeding pro-
tocols for bone tissue engineering strategies requires an integrative approach. This
strategy uses mathematical modeling to explain a mechanism of biomaterial-cell
interactions in combination with experimental research to provide data for the de-
termination of the model parameters as well as the validation of the model [ 5 ].
Moreover, this process is inherently iterative, where new experimental results can
be fed to the model and thorough model analysis can lead to new research hypothe-
ses.
4 Prospects
Most of the current models look either at mechanoregulatory or bioregulatory stim-
uli, depending on the specific research question that is being answered. In the future,
however, these models could be combined to further improve the predictive capabil-
ities of the model. Another issue is the specific scale at which most models are cre-
ated. Some models look in more detail at a small scale (e.g. [ 11 ]) while others look
at a larger scale [ 8 , 15 ]. The problem of bone regeneration inside (CaP) scaffolds is
however regulated by countless biochemical and mechanical factors across multiple
organizational scales. The time scales of these individual events range from seconds