Computational approaches for ageing and age-related diseases

Photo credit: ICM Centre for neuroinformatics

1 & 2 September 2020

Paris Brain Institute (ICM)

Pitié Salpétrière Hospital
47 boulevard de l’Hôpital
75013 PARIS

Compage becomes virtual

  • Registrations are now open! Free but compulsory here

Keynote speakers

  • Mihaela van der Schaar (University of Cambridge and The Alan Turing Institute)
  • Adam Schwarz (Takeda Pharmaceuticals)

Projects highlights

  • EuroPOND by Daniel Alexander (University College London)
  • Radar-AD by Martin Hofmann-Apitius (Fraunhofer Institute)

Research topic in Frontiers in AI – Medicine and public health

This workshop is linked with a dedicated research topic in Frontiers in Artificial Intelligence – Medicine and public health.

You are welcome to submit your paper whether you submitted to CompAge or not.


(Time is in Central European Summer time (UTC+2). In other words, the time it is in Paris, France)

Day 1- Tuesday 01/09/2020

8:45 – 9:00Welcome messageS. Durrleman (Paris Brain Institute – ICM)
9:00 – 9:30Europond highlightsD. Alexander (UCL)
9:30 – 10:00Piloting a novel screening tool for reducing heterogeneity in clinical trials in Alzheimer’s diseaseN. Oxtoby (UCL)
10:30 – 11:30KeynoteMihaela van der Schaar (university of Cambridge & The Alan Turing Institute)
11:30 – 12:00Prediction of biomarkers’ trajectory in Huntington’s disease: application to precise clinical trial designI. Koval (Paris Brain Institute – ICM); T. Dighiero; R. Scahill; A. Durr; S. Durrleman
12:00 – 12:30Event-based modelling of multimodal biomarkers in multiple sclerosisV. Wottschel (Amsterdam UMC); I. Dekker; M. Schoonheim ; V. Venkatraghavan; A. Eijlers; I. Brouwer; E. Bron; S. Klein; M. Wattjes; J. Geurts; B. Uitdehaag; N. Oxtoby;  D. Alexander; H. Vrenken; J. Killestein; F. Barkhof

Lunch Break

 Machine Learning/Deep Learning 
14:00 – 14:30Application of Variational Autoencoder Modular Bayesian Networks (VAMBN) in assessing role of functional and cognitive decline in observational cohortsM. Sood (Fraunhofer SCAI); M. Hofmann-Apitius; H. Fröhlich
14:30 – 15:00Deep learning for clustering of multivariate longitudinal clinical patient data with missing valuesJ. de Jong (UCB Biosciences GmbH)
15:30 – 16:00Generating Images that Mimic Disease ProgressionD. Ravì (UCL); D. Alexander; N. Oxtoby
16:00 – 16:30Aging Human Avatar: a computational modeling platform to study neural correlates of agingD. Sheynikhovich (Institut de la Vision)
16:30 – 17:30Posters

Interactive session

Day 2 – Wednesday 02/09/2020

9:00 – 9:30Combining magnetic resonance imaging and magnetoencephalography enhances modeling of brain age

D. Engemann (INRIA); O. Kozynets; D. Sabbagh; G. Lemaître; G. Varoquaux; F. Liem; A. Gramfort

9:30 – 10:00Brain-age predicts subsequent dementia in memory clinic patients.F. Biondo (King’s College London/UCL); J. Cole
 Prediction models 
10:30 – 11:00Forecast of the MMSE score up to 6 years ahead, with cross-cohort replicationsE. Maheux (INRIA / Paris Brain Institute – ICM); I. Koval; S. Durrleman
11:00 – 11:30Comparison of Alzheimer’s Disease Progression Patterns across Multiple Cohort Study DatasetsY. Salimi (Fraunhofer Institute for Algorithms and Scientific Computing); C. Birkenbihl; M. Hofmann-Apitius; H. Fröhlich
11:30 – 12:30PostersInteractive session
 Lunch break 
 Industry session 
14:00 – 14:30Radar-AD highlightsM. Hofmann-Apitius (Fraunhofer SCAI, Bonn-Aachen International Center for Information Technology)
14:30 – 15:00Reliable MRI volumetry for Alzheimer’s disease: diagnostic performance of icobrain dm on real-world dataM. Wittens (Uantwerpen); A. Ribbens; D. Sima; W. van Hecke; E. de la Rosa; D. Smeets; S. Engelborghs
15:30 – 16:30Keynote

Adam Schwarz (Takeda Pharmaceuticals)

16:30 – 17:30 Industry Round TableModerator: M. Hofmann-Apitius (Fraunhofer SCAI, Bonn-Aachen International Center for Information Technology)

Aims and scope

Ageing is a complex phenomenon that remains poorly understood and raises great challenges for science, medicine, and society. Age-related diseases, such as neurodegenerative diseases, remain largely uncured, with attrition rates in clinical trials reaching unprecedented levels. There is no consensus on prevention measures due to limited understanding of the complex interplay between the multiple manifestations of ageing across scales, systems and organs. The spectrum of possible trajectories of healthy and pathological ageing is extraordinarily entangled, multifactorial, and heterogeneous.

Describing, modelling, and predicting the progression of slowly evolving biological processes requires the development of specific computational and data-driven methods at the cross-roads of biostatistics, machine learning, mathematical modelling, knowledge modeling and numerical simulation.

CompAge 2020 aims to be a first-of-its-kind forum to communicate recent methodological advances in this field, and foster interactions among researchers from academia, pharmaceutical and technology industries, clinical research, and public health sectors.

Topics of interest include, but are not limited to:

  • Methods to describe, classify and represent the heterogeneity of individual trajectories of ageing from multimodal and longitudinal data sets, with the aim for instance, to understand how genetic, life-style or environmental factors affect ageing;
  • Dynamical models of disease progression integrating various clinical or preclinical data across scales and organs, including omics, cellular and medical imaging, physiological, cognitive, behavioral, and clinical assessments in health or disease, in humans or animal models;
  • Mechanistic models of disease progression, such as pathogen spreading models in neurodegenerative diseases;
  • Development of data-driven tools for precision medicine including personalised prediction of risks, prediction of future adverse events, and recommendations of personalised prevention or therapeutic strategies;
  • Development of novel strategies for the identification, screening and stratification of at-risk population, including the use of digital devices or sensor data;
  • Development of new clinical trial design to assess the efficacy of disease modifying agents in progressive diseases, including methods for simulation of treatment effects on ageing or disease progression;
  • Methods for the analysis of epidemiological or real world data sets with the aim to identify risk factors, or assess long-term efficacy of public health policies.

We encourage contributions from early career researchers from academia and industry.

CompAge 2020 will be the final workshop of the EuroPOND* project, funded within the Horizon 2020 program of the European Union, and the follow-up of a disease progression modelling workshop funded by several Innovative Medicines Initiative (IMI) projects.

CompAge 2020 is committed to providing an atmosphere that encourages the free expression and exchange of ideas. Consistent with this commitment, CompAge 2020 adopts the Code of Conduct of the MICCAI Society. CompAgeg 2020 is endorsed by the MICCAI Society.

Organizing Committee

With the support of

* This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 666992