Biomedical Engineering Reference
In-Depth Information
10.
Multiscale Computational Engineering
of Bones: State-of-the-Art Insights for
the Future
Melissa L. Knothe Tate
a
10.1 Introduction
silico model for the numerous experimental
studies that would be necessary to predict how
loss of the blood supply affects cell viability,
recruitment of progenitor cells, etc. In reality,
one model rarely suffi ces to unravel the
research question at hand. Although in vivo
studies are needed to measure the relevant
parameters, they are inherently limited due to
fi nancial and time constraints. A computa-
tional model based on realistic parameters can
forecast responses to changes in experimental
variables and determine the experimental
approaches that will most likely answer a spe-
cifi c research question. Hence, the fi rst goal of
this chapter is to describe the
strengths of
computational modeling approaches, when
used in tandem with experimental approaches,
to unravel the most enigmatic research ques-
tions of bone biology.
In addition to increasing understanding of
biological system dynamics, in silico computer
models provide an ideal approach to optimizing
experimental design prior to implementation
and testing. This not only improves effi ciency,
but may lead to engineering more functional
tissue prototypes. Tissue models are designed
to optimize a specifi c function that is to be
replaced; by building predictive computational
models, it is possible to determine key para-
meters that infl uence the specifi c function(s) to
be replaced. The second goal of this chapter is
to
outline the process of rational tissue design
and optimization, using as example how a
Computational models provide a platform that
is equivalent to an in vivo, in vitro, and in situ
or ex vivo model platform. Indeed, the National
Institutes of Health have made the development
of predictive computational models a high pri-
ority of the “Roadmap for the Future” (http://
nihroadmap.nih.gov/overview.asp; see espe-
cially “New Pathways to Discovery”). The power
of computational models lies in their useful-
ness to predict which variables are most likely
to infl uence a given result, simulation of the
system response to changes in that variable,
and optimization of system variables to achieve
a desired biological effect. Typically, these
models are computer representations of the
actual system, based on experimentally deter-
mined parameters and system variables;
increasingly these computer models are referred
to as in silico models (Fig.
).
For example, if one were interested in the
role played by the intramedullary blood supply
on bone regeneration in a segmental long-bone
defect, it might be possible to substitute an in
10
.
1
a
Based on the work from Dr. Knothe Tate's research team
(carried out by former and current students, including
Eric J. Anderson, Steven Kreuzer, Hans-Jörg Sidler, Adam
Sorkin, Roland Steck, and Andrea Tami) and the clinical
and research practice of Ulf R. Knothe, M.D., D. Sc. This
chapter is dedicated to my team.
141
