Modelling and simulation environment for systems medicine (Chronic obstructive pulmonary disease -COPD- as a use case)

Synergy will develop a simulation environment and a decision-support system aiming at enabling deployment
of systems medicine. The three core elements are a knowledge base (KB), an inference engine (IE), and a
graphical visualisation environment (GVE). The project focuses on patients with chronic obstructive pulmonary
disease (COPD).
The KB will include five well established physiological models addressing: 1) Central and peripheral O2 transport
and utilization, 2) Pulmonary gas exchange, 3) Regional-lung heterogeneities in ventilation and perfusion, 4)
Skeletal muscle bioenergetics, and 5) Mitochondrial reactive oxygen species (ROS) generation. These models
will be written in systems biology markup language (SBML) and vertically integrated. Ontologies will be used
as the default knowledge-representation system. The KB will include multi-level data from experimental studies
(BioBridge), data from a multicentre longitudinal study on COPD phenotyping (PAC-COPD) and public datasets.
The IE will enable to explore associations over the KB, perform transversal multi-scale model integration and
related simulations including interactions among O2-availability/O2-utilization, ROS generation, systemic
inflammation and abnormal tissue remodelling.
The Web-based GVE will facilitate relevant simulations in a more intuitive way with respect to the state of the art,
addressing two main user profiles: bio-researchers and clinicians.
The focus will be on underlying mechanisms of COPD phenotypes associated with poor prognosis. Disease
model validation and refinement will be done using a well-established, large dataset (ECLIPSE) together with
experimental studies designed to test “in silico” generated hypotheses. Besides the use of the simulation
environment by bio-researchers for optimal experimental design, the Synergy platform will be a relevant
decision-support tool for integrated healthcare strategies aiming at modulating the evolution of COPDs.