Page 341 - Advances in Biomechanics and Tissue Regeneration

16.7 CONCLUSIONS 339

3.7e+05
350,000
300,000
250,000
200,000
P2
150,000
100,000
50,000
-4.4e+02
(A)

3.7e+05
350,000
300,000
250,000
200,000
P2
150,000
100,000
50,000
-4.4e+02
(B)

3.7e+05
350,000
300,000
250,000
200,000
P2
150,000
100,000
50,000
-4.4e+02
(C)
FIG. 16.12 Evolution of dead cells in the culture chamber (in cell/mL). (A) t ¼ 0 s; (B) t ¼ 42 h; (C) t ¼ 70 h.

Coupling between organ-on-chip platforms and in silico simulations is a two-way knowledge generator. First, it
offers the possibility of trying, once a tumor population has been sufficiently well characterized in terms of a paramet-
ric mathematical model, “what if” conditions, predicting tumor evolution and therefore patient prognosis, and explor-
ing therapies (drugs, chemotherapy, radiotherapy) or surgical intervention. Second, it allows the biologist to speed up
the experimental designs and set up, offering the possibility of an in silico design of the geometry and stabilizing the
conditions of the experiment. In this chapter, both possibilities have been illustrated with two examples of application:
an accurate characterization of cell culture evolution and a computational forecast of an experiment with a given
set up.
However, the richness and complexity of the microenvironment physics results in the growing need for more spe-
cific devices and a major data assimilation from experiments, which in turn should feed in a proper way the compu-
tational models. Integration between data and simulations based on models that maintain the physics of the problem is
a promising opportunity, which shows a trade-off between the power of data science techniques and the underlying
knowledge of the universe that physics brings to us. In the rise of these techniques, which is a hot research area today,
and the application to the clinical field, is the path of patient-specific medicine.

Acknowledgments
The authors gratefully acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness under the projects (MINECO
MAT2016-76039-C4-4-R, AEI/FEDER, UE) and (MINECO BIO2016-79092-R, AEI/FEDER, UE), of the Government of Aragon (DGA-T24_17R) and
of the Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), financed by the Instituto de Salud
Carlos III with assistance from the European Regional Development Fund.

II. MECHANOBIOLOGY AND TISSUE REGENERATION