The School brought together students with a background in life science, bioengineering, human and veterinary medicine and computational mathematics from a wide range of countries inside and outside Europe.
The CompMed School aims to use a systemic approach for the study of the underlying mechanisms of a CD’s phenotypes associated with poor disease prognosis. Based on disease mechanisms, rather than on the current syndrome approach, CompMed aims to be rooted in a molecular description of states of disease that will allow the description of disease phenotypes as caused by dysfunctional networks of molecules. In this context, Systems Medicine (SysMed) shows high potential to build-up novel disease taxonomies, resulting in innovative preventive and therapeutic strategies. SM works on identifying biological/environmental markers in order to enroll individuals at high risk for developing a disease in special early detection trials. It is expected that SM approach will change patient stratification in clinical practice and will drive a more predictive, more preventive, more personalized, and more participative medicine (P4 Medicine).
Content covers the fundamentals of physiological and clinical processes, along with core medical principles, clinical research methods, and trials design, as well as basics of applied mathematics and computing. The program culminates in a capstone design-project in which students work in interdisciplinary teams co-advised by faculty members and investigators from industries and hospitals. The two main biomedical focuses are the study of systemic effects of COPD (i.e. skeletal muscle dysfunction) and the analysis of determinants of co-morbid conditions that are most often associated with COPD (i.e. cardiovascular diseases, diabetes and lung cancer), both clearly associated with poor patient prognosis.
CompMed is an intensive programme of lectures followed up by practical sessions (experiments, computer simulation and modeling) and interdisciplinary group work. The School is based on complex problem solving, using a dynamic approach of the COPD as Case Study. Courses will be given by international experts from France, Spain, the US, the Netherlands, Sweeden and representatives from industry and regulatory bodies. The working language of the school is English.
Know the definition of biological/pathological process; chronic disease; electronic health records; semantic data, mathematical modelling; Investigate biological/pathological process;
Learn how design theoretical models; integrate multi-scale modelling; support interaction between deterministic model and probabilistic models; study perturbations of a biological process; explore the toolbox of biomathematics modelling.
Study data representation and integration; explore semantic technologies and translational medicine; assess data warehouse solutions in terms of their targeted medical use case : data sharing, data interoperability and knowledge discovery.
Discover and manage databases; Use specific and publically available datasets (BioBridge and PAC-COPD); Create semantic mapping on inference engineering; Analyse associations of co-morbidities in PAC_COPD and in the Medicare database (diseasome)
Integrate oxygen transport models from atmosphere to cell with mitochondrial reactive oxygen species (ROS) generation and metabolic pathways.
Provide intuitive users interfaces for clinician and bio-researchers.