HPC/Exascale Center of Excellence in Personalised Medicine

Logo PerMedCoE
Francisco Javier Nieto
Funding Program
H2020 h2020
Project Date

Personalised Medicine (PerMed) opens unexplored frontiers to treat diseases at the individual level combining clinical and omics information. However, the performances of the current simulation software are still insufficient to tackle medical problems such as tumour evolution or patient-specific treatments. The challenge is to develop a sustainable roadmap to scale-up the essential software for the cell-level simulation to the new European HPC/Exascale systems. 

The goal of PerMedCoE is to provide an efficient and sustainable entry point to the HPC/Exascale-upgraded methodology to translate omics analyses into actionable models of cellular functions of medical relevance. It will accomplish so by

  1. optimising four core applications for cell-level simulations to the new pre-exascale platforms
  2. integrating PerMed into the new European HPC/Exascale ecosystem, by offering access to HPC/Exascale-adapted and optimised software
  3. running a comprehensive set of PerMed use cases
  4. building the basis for the sustainability of the PerMedCoE by coordinating PerMed and HPC communities, and reaching out to industrial and academic end-users, with use cases, training, expertise, and best practices.
Our role

Atos will collaborate in the activities related to software optimisation, and will contribute to the definition of the architecture and the workflows in HPC/HPDA. Moreover, Atos leads the WP for sustainability and business plan, and has an important role in the dissemination of results and engagement with the industrial community.

Example of the framework that enables multiscale simulations.
Logo PerMedCoE

PerMedCoE: Exascale-ready cell-level simulations for European Personalised Medicine

Coordinated by the Barcelona Supercomputing Center (BSC) and funded by the European Commission, this recently launched HPC centre of excellence will optimise codes for cell-level simulations in HPC