EPSRC logo

Details of Grant 

EPSRC Reference: EP/X019446/1
Title: CompBioMedX: Computational Biomedicine at the Exascale
Principal Investigator: Coveney, Professor P
Other Investigators:
Townsend-Nicholson, Professor A Luthert, Professor PJ
Researcher Co-Investigators:
Project Partners:
ARM Ltd AstraZeneca Atos UK&I
Barcelona Supercomputing Center Cancer Research UK Dassault Systemes
Devices for Dignity DiRAC (Distributed Res utiliz Adv Comp) Evotec (UK) Ltd
Federal University of Juiz de Fora Frederick National Lab for Cancer Res John Radcliffe Hospital
Leibniz Supercomputing Center NIMS University nVIDIA
Rutgers State University of New Jersey SURF Uni Hospital Southampton NHS Fdn Trust
Department: Chemistry
Organisation: UCL
Scheme: Standard Research
Starts: 01 December 2022 Ends: 30 November 2024 Value (£): 406,428
EPSRC Research Topic Classifications:
Parallel Computing Software Engineering
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
EP/X019276/1 EP/X019411/1
Panel History:
Panel DatePanel NameOutcome
14 Sep 2022 SPF Investigate HPUC for exascale software Phase two Interview Announced
Summary on Grant Application Form
Computational biomedicine offers many avenues for taking full advantage of emerging exascale computing resources and, as such, will provide a wealth of benefits as a use-case within the wider ExCALIBUR initiative. These benefits will be realised not just via the medical problems we elucidate but also through the technical developments we implement to enhance the underlying algorithmic performance and workflows supporting their deployment. Without the technical capacity to effectively utilise resources at such unprecedented scale - either in large monolithic simulations spread over the equivalent of many hundreds of thousands of cores, in coupled code settings, or being launched as massive sets of tasks to enhance drug discovery or probe a human population - the advances in hardware performance and scale cannot be fully capitalised on. Our project will seek to identify solutions to these challenges and communicate them throughout the ExCALIBUR community, bringing the field of computational biomedicine and its community of practitioners to join those disciplines that make regular use of high-performance computing and are also seeking to reach the exascale.

In this project, we will be deploying applications in three key areas of computational biomedicine: molecular medicine, vascular modelling and cardiac simulation. This scope and diversity of our use cases mean that we shall appeal strongly to the biomedical community at large. We shall demonstrate how to develop and deploy applications on emerging exascale machines to achieve increasingly high-fidelity descriptions of the human body in health and disease. In the field of molecular modelling, we shall develop and deploy complex workflows built from a combination of machine learning and physics-based methods to accelerate the preclinical drug discovery pipeline and for personalised drug treatment. These methods will enable us to develop highly selective small molecule therapeutics for cell surface receptors that mediate key physiological responses. Our vascular studies will utilise a combination of 1D, 3D models and machine learning to examine blood flow through complex, personalised arterial and venous structures. We will seek to utilise these in the identification of risk factors in clinical applications such as aneurysm rupture and for the management of ischaemic stroke. Within the cardiac simulation domain, a new GPU accelerated code will be utilised to perform multiscale cardiac electrophysiology simulations. By running large populations based on large clinical datasets such as UK Biobank, we can identify individual at elevated risk of various forms of heart disease. Coupling heart models to simulations of vascular blood flow will allow us to assess how problems which arise in one part of the body (such as the heart) can cause pathologies on remote regions.

This exchange of knowledge will form a key component of CompBioMedX. Through this focussed effort, we will engage with the broader ExCALIBUR initiative to ensure that we take advantage of the efforts already underway within the community and in return reciprocate through the advances made with our use case. Many biomedical experts remain unfamiliar with high-performance computing and need to be better informed of its advantages and capabilities. We shall engage pro-actively with medical students early in their career to illustrate the benefits of using modelling and supercomputers and encourage them to exploit them in their own medical research. We shall engage in a similar manner with undergraduate biosciences students to establish a culture and practice of using computational methods to inform the experimental work underpinning the basic science that is the first step in the translational pathway from bench to bedside.

Key Findings
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Potential use in non-academic contexts
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Description This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Date Materialised
Sectors submitted by the Researcher
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Project URL:  
Further Information:  
Organisation Website: