COSMIC Mission

COSMIC delivers the next generation of systems medicine professionals who successfully combat complex human disorders. We will focus on B-cell lymphoma and rheumatoid arthritis, diseases that originate from abnormal functioning of the adaptive immune system, in particular the germinal center. COSMIC develops and integrates experimental and computational approaches, and establish a unique cross-fertilization between oncology and auto-immunity. 
Download: COSMIC Summary
  • COSMIC in numbers

    10 Beneficiaries
    7 Partner Organisations
    14 Early Stage Researchers (ESRs)
        -13 PhD students
        -1 Industrial researcher
    5 Companies
    9 European countries
        -NL, FR, SE, UK, IT, ES, DE, CH, EL
    5 Visiting Scientists
    4 External Trainers
    5 Members of External Advisory Board
    1 Ethics Advisor
  • COSMIC Research Background

    Systems Medicine

    One of the key question in systems biology is how biological systems (e.g., cells, molecular networks, germinal center) operate upon interaction with their external environment. Answering this question will generate knowledge about the dy­namics of complex systems and quantitative and explanatory computer models based on ex­perimental data.

    Systems medicine implements systems biology approaches in medical research and practice. This involves iterative and reciprocal feedback between clinical investigations and practice with computational, statistical and mathematical multiscale analysis and modelling of pathogenetic mechanisms, disease progression and remission, treatment responses, and adverse events as well as disease prevention at the individual patient level.

    Systems medicine aims at a measurable improvement of patient health through systems-based approaches and practice.

    Source: CASyM
    See also: EASyM
    Further reading: Schmitz, U., and Wolkenhauer, O. eds. (2016). Systems Medicine (New York: Springer)

    Adaptive immunity
    Germinal Center
    B-cell lymphoma
    Rheumatoid Arthritis
    Computational modelling
  • COSMIC Systems Medicine

    Through collaboration with existing systems medicine initiatives (e.g. EASyM, ISBE) COSMIC researchers contribute to systems medicine infrastructure and best practices that reduce time and costs to address clinical needs.

    At the same time this will promote Europe’s position in the health domain.
  • COSMIC Training

    An important aim of the Marie Sklodowska-Curie Action European Training Network (ETN) is to train young researchers (Early Stage Researchers, ESRs) with multi-disciplinary and multi-sectorial scientific and transferable skills required in systems medicine and translational medicine (WP2).

    COSMIC delivers 14 highly skilled systems medicine professionals who are able to address and solve complex clinical questions and to shape the next generation of systems medicine scientists.

Work package 5.  Computational modelling

Work package leader: Prof. dr. Michael Meyer-Hermann.


Research question: How to develop and use computational disease models to gain insight in the role of the germinal center reaction (GCR) in B-cell lymphoma (BCL) and rheumatoid arthritis (RA)?


We address three key challenges to develop new hypotheses about the role of the GCR in BCL and RA. Firstly, the development of models that explicitly include (putative) disease mechanisms. Secondly, we will investigate how these models can optimally make use of the experimental data from a wide range of experimental technologies and sources (WP3 and WP4). Thirdly, how to combine different computational modelling formalisms. Models will be validated by dedicated experiments in WP3 and WP4 (complemented with data from public repositories), and interpretation of WP3 and WP4 data will be supported by the computational models. The iterative process between computational modelling and experiments is expected to elucidate and characterise molecular and cellular defects of the GCR in BCL and RA. The models will include different components including B cells, Tfh cells, FDCs, transcription factors, and oncogenes. We will integrate different modelling formalisms. Novel deep machine learning approaches will be used for the construction of phenomenological interaction networks and knowledge graphs (e.g. from omics (public) data, literature) that comprise integrated components (e.g., genes, epigenetics, phenotypic information) for normal and diseased conditions, time-points, and/or species. These networks will identify key determinants of the GCR in BCL/RA and provide input for the mechanistic models. Dynamic mechanistic models will be implemented as agent-based models (ABM) or as Ordinary Differential Equations (ODEs). Briefly, ODEs are used to study to overall dynamics of the GCR (cellular and molecular level) by representing its continuous components (e.g., transcription factors) as equations. In contrast, ABMs provide a direct (lattice-based) representation to study the dynamics of the GC at the cellular level by modelling properties and behaviour of individual agents (e.g., B cells). ABMs are more suitable to model temporal and spatial dynamics simultaneously. Additionally, we will use Partial Differential Equations to model GC chemokine gradients, and cellular Potts models to incorporate cell volumes. Mechanistic probabilistic models based on the description of genes as Piecewise Deterministic Markov Processes are used to infer gene regulatory networks (GRN) from single cell data.

COSMIC aims to develop multiscale models that integrate the cellular level (e.g., B cells) with the molecular level (e.g., GRNs within these cells), to investigate the effect of (disturbed) molecular pathways on the GC B-cell population. 

Expected results: (multiscale) models and insights of the role of the GCR in BCL/RA. Putative biomarkers and drug targets that will be tested in sillico and in WP3 and WP4


Go to Work package overview 


29 April 2018 3358

EASyM conference

2nd Conference of the European Association of Systems Medicine (EASYM) This conference is…
27 January 2018 2968

Andien Vaes: new controller

New controller: Andien Vaes. Andien Vaes (AMR) takes over the tasks of Don van Velzen.…
23 December 2017 852

Biotecture becomes Science Matters

Biotecture becomes Science Matters Our Partner Organisation Biotecture changed their name…

COSMIC Highlights

29 September 2019 74

LINK - Extremadura en el Mundo

LINK - Extremadura en el Mundo Our fellow, Rodrigo Garcia Valiente took part as an…
22 February 2019 301

CERTH Highschool students

Highschool students at CERTH Rerun by popular demand. Bastien of PLANT.ID did so well…
11 February 2018 1865

COSMIC Coffee Mug

First COSMIC Merchandise During the kickoff meeting (8-9 February) all participants…


06 May 2018 763

5th European Congress of Immunology

5th European Congress of Immunology 2-5 september 2018 | Amsterdam RAI Exhibition and…
29 April 2018 1267

EASyM 2nd conference

2nd Conference of the European Association of Systems Medicine (EASYM) 7 - 9 November…
16 March 2018 2510

Workshop Applying bioinformatics and data science competency frameworks to ELIXIR Training

Workshop Applying bioinformatics and data science competency frameworks to ELIXIR…


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    Project coordination

    Prof. dr. A.H.C. van Kampen (Antoine)
    Bioinformatics Laboratory
    E: a.h.vankampen at
    P: +31 20 5667096

    Project management:
    Dr. Laurian Jongejan
    Department of Experimental Immunology
    E: l.zuidmeer at
    P: +31 20 5666819

    The Netherlands
    Academic Medical Center, University of Amsterdam

    Marie Skłodowska-Curie Actions

    The Marie Skłodowska-Curie actions (MSCA), named after the double Nobel Prize winning Polish-French scientist famed for her work on radioactivity, support researchers at all stages of their careers. One type of action is the European Training Network (ETN) aimed at joint research training by partners from academia, industry, and other organisation. ETNs facilitate the the researcher to experience different sectors and develop their transferable skills by working on joint research projects.


    COSMIC is a European Training Network funded from the European Union's Horizon 2020 research and innovation programme under grant agreement No 765158.

© 2018 COSMIC. All Rights Reserved.

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