CompBioMed

EPCC is a Core Partner of CompBioMed, a European Centre of Excellence focused on the use and development of computational methods for biomedical applications. We prepare these applications for future exascale systems, to create the first virtual humans: digital twins to enable personalised medicine.

Simulation of running human

We support medical scientists from both academia and industry, ie hospitals and medical research institutions, who research three main scientific areas: cardiovascular medicine, molecular-based medicine (including COVID-19 research), and neuro-musculoskeletal medicine.

EPCC provides access and support to CompBioMed users on the Cirrus and ARCHER2 systems, but also assists in preparing their applications for future exascale platforms. We are active in CompBioMed’s training activities and coordinate its e-Seminar series.  EPCC also engages with potential new users, offering free access to CompBioMed services, including porting, parallelising, and scaling biomedical applications to supercomputers.

We also support those interested in enabling workflows that require safely moving sensitive data, following FAIR data principles, to large computers for processing via traditional HPC simulations and/or machine learning. Through a collaboration with the LEXIS consortium, we are investigating a particularly exciting new workflow we have named Resilient HPC, designed for urgent, safety-critical Exascale computations.

Coronavirus research 

CompBioMed is active in a large international consortium across Europe and USA working on urgent coronavirus research. To date, the consortium has redirected substantial research effort and funding into computational investigations that has improved our understanding of the SARS-CoV-2 virus and the associated COVID-19, and has accelerated the development of treatment options, including antiviral drugs and vaccines.

The work of the consortium includes bioinformatics analysis and simulation, molecular modelling, electronic structure calculations, epitope analysis, machine learning, epidemiological studies, and the creation and hosting of a growing collection of relevant datasets.

Project details

Funding
The European Union’s Horizon 2020 research and innovation programme, grant agreement No 675451 (phase 1) and grant agreement No. 823712 (phase 2).
Runtime
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Project partners

Project partners are drawn from a wide range of universities across Europe and the USA. 

Project contact

Dr Gavin J Pringle
Dr Gavin Pringle