CompBioMed2

A Centre of Excellence in Computational Biomedicine

CompBioMed is a user-driven Centre of Excellence (CoE) in Computational Biomedicine, designed to nurture and promote the uptake and exploitation of high performance computing within the biomedical modelling community. Our user communities come from academia, industry and clinical practice.

The first phase of the CompBioMed CoE has already achieved notable successes in the development of applications, training and efficient access mechanisms for using HPC machines and clouds in computational bio-medicine. We have brought together a grow-ing list of HPC codes relevant for biomedicine which have been enhanced and scaled up to larger machines. Our codes (such as Alya, HemeLB, BAC, Palabos and HemoCell) are now running on several of the world’s fastest supercomputers and investigating challenging applications ranging from defining clinical biomarkers of arrhythmic risk to the impact of mutations on cancer treatment.
Our work has provided the ability to integrate clinical datasets with HPC simulations through fully working computational pipelines de-signed to provide clinically relevant patient-specific models. The reach of the project beyond the funded partners is manifested by our highly effective Associate Partner Pro-gramme (all of whom have played an active role in our activities) with cost free, light-weight joining mechanism, and an Innovation Exchange Programme that has brought up-ward of thirty scientists, industrialists and clinicians into the project from the wider community.

Furthermore, we have developed and implemented a highly successful training pro-gramme, targeting the full range of medical students, biomedical engineers, biophysics, and computational scientists. This pro-gramme contains a mix of tailored courses for specific groups, webinars and winter schools, which is now being packaged into an easy-to-use training package.

In CompBioMed2 we are extending the CoE to serve the community for a total of 7 years. CompBioMed has established itself as a hub for practitioners in the field, successfully nucleating a substantial body of research, education, training, innovation and outreach within the nascent field of Computational Biomedicine. This emergent technology will enable clinicians to develop and refine personalised medicine strategies ahead of their clinical delivery to the patient. Medical regulatory authorities are currently embracing the prospect of using in silico methods in the area of clinical trials and we intend to be in the vanguard of this activity, laying the ground-work for the application of HPC-based Computational Biomedicine approaches to a greater number of therapeutic areas. The HPC requirements of our users are as diverse as the communities we represent. We support both monolithic codes, potentially scaling to the exascale, and complex workflows requiring support for advanced execution patterns. Understanding the complex outputs of such simulations requires both rigorous uncertain-ty quantification and the embrace of the convergence of HPC and high-performance data analytics (HPDA). CompBioMed2 seeks to combine these approaches with the large, heterogeneous datasets from medical records and from the experimental laboratory to underpin clinical decision support systems. CompBioMed2 will continue to support, nurture and grow our community of practitioners, delivering incubator activities to prepare our most mature applications for wider usage, providing avenues that will sustain CompBioMed2 well-beyond the pro-posed funding period.

PROJECT’S CONTACT:

Emily Lumley

H2020 Centre of Excellence

Call:
INFRAEDI-02-2018

Coordinating Organization:
University College London, United Kingdom

Project Timespan
2019-10-01 – 2023-09-30

Other Partners:
  • Universiteit van Amsterdam, Netherlands
  • EPCC – The University of Edinburgh, United Kingdom
  • BSC – Barcelona Supercomputing Center, Spain
  • SURF, Netherlands
  • University of Oxford, United Kingdom
  • University of Geneva, Switzerland
  • The University of Sheffield, United Kingdom
  • CBK Sci Con Ltd, United Kingdom
  • Universitat Pompeu Fabra, Spain
  • Bayerische Akademie der Wissenschaften / Leibniz Rechenzentrum (LRZ), Germany
  • Acellera, Spain
  • Evotec Ltd, United Kingdom
  • Atos (Bull SAS), France
  • Janssen Pharmaceutica, Belgium
  • UNIBO – Alma mater studiorum – Universita di Bologna, Italy