Biomedical Engineering Reference
In-Depth Information
dynamic: These are feedback control, structural stability, redundancy, modularity,
and adaptation [
42
-
44
]. Because biological systems are multiparametric, complex,
and dynamic it can easily be recognized that complex diseases such as cancer or
asthma are not monocausal. Diagnosis as well as treatment and prevention deci-
sions must be based on this nature of biological systems and the individuality of
patients, demanding tools to support health professionals for optimal use of the
knowledge [
41
].
Modeling approaches help us understand the function and behavior of these
highly complex biological systems, and also support predictions for parameters or
situations that are not possible to measure and analyse with current methods.
Therefore, modeling approaches are also recognized as powerful tools in future
medicine to integrate the available data of a patient and support health profes-
sionals in their decision making. The translation of these novel approaches into
clinical application will allow a general practitioner or a clinician to identify the
optimal medical therapy or prevention treatment for each person based on the
individual data that are available.
4 The 'IT Future of Medicine' Approach
The international research consortium 'Information and Communication Tech-
nology for the Future of Medicine' (ITFoM) anticipates the medicine of the future
and is based on molecular, physiological, and anatomical data from all individual
patients. The aim of the ITFoM project is the creation of the 'virtual patient' model
integrating all different layers of genomic, physiological, and other relevant
information to support health professionals in their decision-making process for
therapy and prevention strategies for each individual patient.
ITFoM (
www.itfom.eu
)
is a flagship pilot project developing a research pro-
gramme to achieve truly individualized medicine in 2025. Initiated by a call from
the European Future and Emerging Technologies programme, the ITFoM pilot
connects the experts in Europe and worldwide to address this challenge and enable
data-driven personalized medicine in the future [
4
,
9
,
45
].
Systems biology offers the methodologies and tools to analyse, integrate, and
interpret biological data, providing mathematical concepts, and models, of bio-
logical processes which are then subjected to computational simulations. The
ITFoM project will establish the 'virtual patient' system allowing for integration of
all relevant data not only to improve and facilitate personalized medicine, but also
enabling the prediction of the consequences of lifestyle choices and medical
interventions on a tailored case-by-case basis.
To implement this vision and see the use of 'virtual patients' become part of
standard clinical practice, substantial advances must be made in underpinning
hardware and software infrastructures, computational paradigms, and human-
computer interfaces, as well as in the instrumentation and automation of tech-
niques required to gather all relevant information useful for the model approach.
