Biomedical Engineering Reference
In-Depth Information
and who has access to those data. The legal and ethical framework might differ
substantially between countries, therefore initiatives such as the European Union-
United States eHealth initiative are very important to start a discourse about the
set-up of new systems between countries at the earliest possible stage to facilitate
the mobility of citizens (
http://ec.europa.eu/digital-agenda/en/about-health
)
.
All these technologies contribute to the generation of highly detailed infor-
mation about an individual's genetic make-up and physiological status and allow
unprecedented insight into the functioning of an individual as a whole [
33
].
For all these tools enabling molecular diagnostics it will be highly important to
define generally accepted standards and protocols to eliminate errors and false
responses of the systems. The standardization of all upstream and downstream
processes in molecular diagnostics gain highest priority when the data are inte-
grated in the EHR and the virtual patient model to support decision making in the
clinical routine. Sample preparation, measurements, data generation, data handling
and processing, and mathematical analysis must follow the standards strictly to
avoid false responses or predictions based on the model [
34
-
36
].
3 Systems Medicine: A Paradigm Shift
in Personalized Medicine
Systems biology is a novel approach to decipher biological complexity on a
systems level. In systems biology, methodologies and tools for mathematical
analysis, integration, and interpretation of biological data as well as simulation and
visualization methods are employed to build mathematical models of biological
processes such as cellular interaction networks [
37
-
40
]. The present analytical
tools need enlargement to address more complex questions and the integration of
aspects not yet considered to be relevant, including environmental conditions and
lifestyle data [
41
].
Mathematical models support the integration and interpretation of increasingly
large datasets and combine these with existing knowledge to allow the interpre-
tation of the data. Model approaches have been used widely for pattern recogni-
tion, data mining, and network analysis of complex and heterogenous molecular
data. The novel approach of systems medicine using a virtual patient model will
drive this approach further to reach the level of simulation and subsequent pre-
diction of possible scenarios that cannot be measured directly.
Systems biology represents a complement to the current 'reductionistic' way
that science is performed and how the results are transferred to medicine [
41
]. The
systems approach includes the dynamics and nonlinear behavior of networks in
biological systems. One prerequisite is knowledge about all the components that
are determining and influencing the behavior of a biological system, how they
interact, and their resolution and behavior in space and time. Biological systems
use mechanisms to achieve robustness and stability while being flexible and
