Network: POEMS - Predictive mOdelling for hEalthcare technologies through MathS

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.

Over the next decade, this network will contribute to a national research agenda in the field of predictive modelling for healthcare technology. This will not only impact on the scientific community, but also enable the UK as a whole to retain a competitive edge in the field, exploiting potential of UK science to the full in order to deliver the best possible healthcare to the general population. This ambitious long-term goal is hard to achieve by top-down approaches or managed calls alone. We propose a route towards a long-lasting impact where ideas emerge, grow and interact organically, in the spirit of an EPSRC Sandpit or Ideas Factory. The network we are proposing can deliver these objectives, and without a network of the type we are proposing it is likely that the potential and abilities available in the UK research community will not be exploited to the full.

In the short term (4 years) the network primarily benefits UK-based academics working in modelling for healthcare technologies. The immediate objective is to build up a networked community and to strengthen links where they already exist. A second important group of beneficiaries are end-users: clinicians, and healthcare professionals. Network activities will be developed to specifically include members of this group (e.g. at assemblies, and themed events). A crucial aspect of the network is that the advances in mathematical and computational modelling techniques are informed by the needs of healthcare professionals. Contact with the clinical domain will be made through existing links of the investigators (see pathways to impact document), and more importantly the network will exploit other existing contacts of its membership. There can be no doubt that many of the 200 members we anticipate to include will have such contacts in place, and it is an explicit goal of the project to make the most of these in order to deliver a maximal impact.

In the medium to long-term (5-10 years), technical advances arising from collaborations instigated by the network will benefit healthcare industries (for example, in the development of novel treatments, or drug development). The network will kick start collaborations and result in joint grant proposals. These follow-on grants will ultimately lead to the advances just described. On a similar timescale, this research will be useful to policy makers in setting healthcare agendas and priorities. Within twenty years we anticipate that the use of modelling in healthcare will become more widespread, making treatments more targeted, and therefore more beneficial and cost-effective.

The network will help to focus and to channel research efforts in this field, it will make sure that the community explores the biggest possible set of future research lines, and that the research base, in discussion with clinical practitioners, then selects those avenues which are the most likely to yield exploitable results. Engaging a wide UK community of researchers in this field and using their expertise as an input determining the direction of future research will ensure that future research funding is used as efficiently as possible and is spent on research lines identified by the community as the most promising. For the wider public, long term benefits will be improved healthcare. In the shorter term (four years), public engagement is an important aspect of network activity, communicating ways in which mathematics can have an impact on everyday life. The benefit to the UK economy of this outreach work will be a future generation of mathematicians inspired by the leading-edge advances of this network, communicated through a variety of media (school events, articles in the popular press, use of the Internet).The participants of the network will gain skills they can use in future projects, or apply elsewhere. For example, all members will be expected to hone their communication skills, and media training will be offered to early career members.