In Vivo, In Vitro, In Silico: Computational Tools for Product and Process Design in Tissue Engineering - Computational Modeling in Tissue Engineering - page 6

combined use of experiments and mathematical modelling and describe not only
how the simulation results play an important role in generating information that
can help in unravelling mechanisms that drive solute transport but also genuine
efforts that have been taken to translate this information into real TE set-ups.
Another type of carrier material that is often used, mainly in musculoskeletal
tissue engineering, is a (macro-) porous scaffold. Similar to the hydrogels discussed
above, these scaffolds allow supporting mechanical loading and mass transport.
Olivares and Lacroix [ 34 ] review the computational methods applied to characterize
scaffold morphology and simulate different biological processes in and around these
scaffolds. These processes include cell seeding, cell migration, cell proliferation, cell
differentiation, vascularisation, oxygen consumption, mass transport and/or scaffold
degradation. Song et al. [ 35 ] describe how using a combination of computational
fluid dynamics and finite element analysis allows to predict flow regimes within
scaffolds and to optimize flow rates to deliver mechanical cues during cell seeding
and subsequent cell behaviour. They furthermore demonstrate how computational
modelling can be used to optimize spatiotemporal mechanical cue delivery and
mechanically modulated biochemical gradients through optimization of scaffold
geometry, material behaviour and mechanical properties.
Besides the scaffold's physical properties, also its chemical properties (e.g. its
release properties) can have a substantial influence on the overall behaviour of the TE
construct. Chemicals released form the scaffolds can either be dissolved components
of the scaffold material itself (e.g. the release of soluble calcium from calcium-
phosphate-collagen scaffolds) or substances that were added to the scaffold structure
for delivery in vivo and have a specific biological function (e.g. controlled release of
growth factors). Mathematical models have been developed describing these release
processes and have been applied to determine in silico optimal scaffolds for a variety
of biomedical problems, e.g. Carlier et al. [ 27 ] and many others.
For TE products that include (or are solely consisting of) a cellular component,
models have been developed to investigate aspects ranging from storage over pro-
liferation and selection to implantation strategies. Cincotti and Fadda [ 36 ] describe a
model of the cryopreservation process of cell suspensions, a critical step in tissue
engineering. The model is based on bio-physical properties and takes into account
size distribution of the cell population. After validation, the authors have used their
model to investigate the effect cell size distribution on system behaviour under
various operating conditions showing that under commonly used operating condi-
tions, intra-cellular ice formation may be lethal for the largest cells in the population.
In addition to cell size, cell populations are also heterogeneous in various other
functional and molecular aspects. Galle et al. [ 37 ] review the most recent results on
heterogeneity in mesenchymal stem cells (MSC) and introduce a mathematical
framework that approaches MSC heterogeneity on the single cell level. This
framework is capable of describing the impact of MSC heterogeneity on in vitro
expansion and differentiation and can be used to investigate MSC adaptation to
changing environments and the cell's intrinsic control of state fluctuations. Prior to
implantation, the quality of the cells needs to be assessed in order to guarantee a safe
and effective therapy. As this quality check should preferably be non-invasive,