Computational Medicine for Chronic Diseases


CompMed is an intensive two-weeks school for MSc-PhD students, and young professionals which teaches the analytical tools and methodologies needed to meet the challenge of the P4 Medicine. The goal is to train clinicians, researchers, and engineers in healthcare optimization using computational methods, modeling and simulation relevant to chronic diseases.


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.


CompMed is an interdisciplinary school based on six sessions:

  • 1st session: Semantic mapping of patient-specific data and modeling from ontologies.

– Create a semantic mapping on inference engineering using on ontologies
– Support the multi-scale model integration.
– Support the interaction between deterministic model and probabilistic models.
– Provide intuitive users interfaces for clinician an bio-researchers.
-Use specific datasets (BioBridge and PAC-COPD) and publically available datasets

  • 2nd session: Vertical model integration for mechanistic modeling

– Integrate of different physiological deterministic models explaining oxygen transport from the atmosphere to the cell
– Integrate of oxygen transport models with modeling of mitochondrial reactive oxygen species (ROS) generation
– Prepare the integration between deterministic models of oxygen transport and mitochondrial ROS generation with probabilistic modeling of metabolic pathways

  • 3rd session: Multi-scale horizontal integration

– Use of deterministic and probabilistic modeling to analyze the underlying mechanisms of the three phenotypes identified in the PAC-COPD study
– Analyse of associations of co-morbidities in PAC-COPD and in the Medicare database (diseasome)
– Use of deterministic and probabilistic modeling to assess abnormal regulation of metabolic pathways associated with clustering of co-morbid conditions.

  • 4th session. Tools for bio-researchers and clinicians

– Create an inference engine and a simulation environment, which allow reasoning and computer-based prediction using the knowledge base (WP3)
– Create two graphical visualization environments, which allow a user profile access the simulation engine and the inference engine
– Produce clinical decision support systems to be integrated into an ICT platform supporting integrated care

  • 5th session. Model and platform validation

– Validate of the knowledge generated on underlying factors of COPD phenotypes and determinants of clustering of co-morbid conditions using the ECLIPSE dataset
– Assess the usability and applicability of the prediction models integrated into the ICT platform supporting integrated care

  • 6th session. Communication, dissemination

– Write an executive summary reporting all the aspects to be addressed and containing: o An introduction of the proposed solutions o The 5 deliverables o A discussion and conclusion: the group has to provide a SWOT matrix analyzing their choices and proposition of production
– Prepare an oral defense: Each group will have to prepare slides for an oral defense: 20 minutes for presentation and 15 minutes for questions.

Participants are invited to work on a computer-based simulation environment for prediction of patient prognosis that should facilitate the design of early strategies to modulate the disease progress. The aim is that the physician enters clinical data of the patient and can receive support to predict the effects of a specific rehabilitation therapy obtained from the results of various differential equations and a knowledge-based system. The participants have to design a clinical decision support systems (CDSS) aiming at facilitating clinical applicability of knowledge generated by the project into an integrated care scenario ( The student’s groups are coached by academic and professional tutors from Synergy-COPD consortium.

Learning outcomes
  • 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.
Examination and credits rewarded

6 ECTS are rewarded after taking part in the Oral defense, and after handing over individual assignment (deliverables) two weeks after the Summer School.

Starting material

Different publications and documents on the subject will be downloadable on the intranet of the bioHC website. These documents must be read by students before the Summer School.

  1. GOLD Pocket Guide 2011 and GOLD Report 2011.
  2. Bousquet J et al. 2011. Systems medicine and integrated care to combat chronic noncommunicable diseases. Genome Med. 3:43
  3. Turan N et al. 2011. A systems biology approach identifies molecular networks defining skeletal muscle abnormalities in chronic obstructive pulmonary disease. PLoS Comput Biol; 7:e1002129.
  4. Noble D. 2011. Differential and Integral Views of Genetics in Systems Medicine. Interface Focus. 1;7-15

Ten scholarships are offered by CASyM and Partner Institutions to the best ranked students. They are covering the accommodation and travel expenses.

Deadline for applications

March 1- July 3, 2017

Location and dates

European Scientific Institute, Archamps Technopole (Geneva airport, Suisse)
August 22 – 31, 2017

Partner institution

CompMed is jointly organised, since 2011, by Université Grenoble Alpes, Universitat de Barcelona and European Scientific Institute (Erasmus Mundus Framework Partnership Agreement). CompMed associates the following Partner Institutions: Maastricht University (UM, The Netherland), Karolinska Institutet (KI, Sweeden), UC San Diego (UCSD, US) and Synergy COPD Partners (Eurecat, Biomax, Idibaps, Linkcare, University of Birmingham, Liverpool and Oxford). CompMed’s is transferring outcomes from Synergy-COPD, an EU project funded by the 7th Framework Programme (under grant agreement number 270086,

Image1This school is organized in partnership with the Coordinating Action Systems Medicine (CASyM), which is a multidisciplinary European consortium that joined forces to develop an implementation strategy for Systems Medicine …