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Details of Grant 

EPSRC Reference: EP/L001101/1
Title: Network: POEMS - Predictive mOdelling for hEalthcare technologies through MathS
Principal Investigator: Clayton, Professor RH
Other Investigators:
Shankland, Professor CE Galla, Dr T
Researcher Co-Investigators:
Project Partners:
Department: Computer Science
Organisation: University of Sheffield
Scheme: IDEAS Factory Sandpits
Starts: 01 April 2013 Ends: 31 March 2017 Value (£): 254,355
EPSRC Research Topic Classifications:
Medical science & disease
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
The delivery of healthcare is an increasingly important policy question, given an ageing population, and the need to decrease operating costs. The mathematics, engineering, and physical sciences (EPS) communities have a potentially important role to play in developing new technologies that will enable healthcare to be delivered in a more effective and personalised way. The key to maximising the translation of tools and ideas from the academic research community to clinical practice is engagement and interaction amongst a diverse and multidisciplinary community. This network has arisen from an EPSRC sandpit on Predictive Modelling for Healthcare Technologies Through Maths, and the initial membership of the network will be the sandpit participants. However, a key aim of the network is to grow, connect, and co-ordinate the UK research community working predictive models, well beyond the pool of participants who attended the sandpit, and especially focusing on areas that were under-represented amongst the sandpit attendees. In particular, we will target new members from the clinical, healthcare, mathematics, experimental biology, and industrial communities, with research interests aligned with the network objectives. The proposed size of the network is 200 members.

The overall aim of the network is to be an accelerating mechanism for collaborations and research activity on predictive modelling for healthcare. These in turn will form the building blocks of a wider vision and research agenda on a national scale beyond the lifetime of the network. These goals will be achieved through four main types of activity: network assemblies, themed events, travel grants, and continuous communication within the network using social media.

Network assemblies bracket the overall activity, occuring in the first and last years of the network period. The first network assembly will have the specific the aim of identifying research challenges and initial collaborative groupings. The final network assembly will allow a review of progress made in our overarching research agenda, and be an opportunity to create a road map for the next 10 years of research in predictive modelling for healthcare technologies.

Throughout the period, the network will provide the infrastructure and resources to enable this feltwork of collaborations to be extended to new partners, developed and nurtured to the level where they can deliver publications and funding proposals. Themed events will be proposed by subgroups of the membership, and will focus on particular topics within the research agenda. This allows for an organic bottom-up mechanism by which promising lines of future research will be identified by members of the community. This approach will ensure that all expertise and creativity contained in the UK research base is exploited to the full when shaping the national research agenda in modelling healthcare for the years 2013-2016 and beyond. Travel grants will allow members to invite prestigious visitors to the UK to explore new collaborations. Communication between the network membership will be continuous: we aim to have an active online community, as well as facilitating face-to-face events.

Communication of the value and potential of predictive models in healthcare to academia, end-users and the general public through outreach activities is one of the network objectives. This will be achieved by bidding to organise sessions at national conferences, by outreach to the general public through events such as the British Science Festival, and through engagement with patient groups.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Further Information:  
Organisation Website: http://www.shef.ac.uk