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Alzheimer's disease is the most common form of dementia, with a cost to society estimated at €177 billion per annum across Europe, according to the European Collaboration on Dementia (EuroCoDe) project funded by Alzheimer Europe. Data-based modelling of network structures is a modern approach to study and understand many diseases including dementia. Research carried out at the Institute of Pure and Applied Mathematics (IPAM) at the University of Aberdeen has led to the development, implementation, and testing of novel mathematical algorithms to infer network structures by means of observations of their dynamics. The results of our research have been implemented as part of a software package now offered by the Netherlands-based company BrainMarker to researchers and practitioners across Europe in an online `pay-per-click' platform (section 5.c1 and 5.c4). As such our research generated impact on clinical practitioners in addition to commercial impact.
Brain diseases cost European healthcare agencies approximately €800 billion each year, but are very poorly understood. Neuroscientists and cyberneticists at the University of Reading study how individual brain cells subserve higher cognitive functions, using brain-computer interfaces to understand how individual cells form neuronal networks. This work has engaged the public imagination through mainstream media, attracted investment from pharmaceutical companies whose drug development programmes demand an understanding of how cellular networks function in the brain and enhanced the use of stem cell derived human neural tissue, thereby enabling a reduction in the use of animals in such research.
Researchers at Queen Mary have applied mathematical modelling techniques to understand how and when problems may arise in complex man-made infrastructure networks including electricity, gas, global shipping and haulage networks. Many of these networks have points of vulnerability where a local issue such as an earthquake, a terrorist attack or even a simple engineering problem can bring down widespread areas of the network. Our research and the associated modelling techniques have impacted on organisations including the UK Treasury Office and the European Commission's Joint Research Centres at both Petten and Ispra, where it has been used to inform UK and European policy guidelines and legislation for infrastructure projects.
Research by Professor Karl Friston at UCL has led to the development of Statistical Parametric Mapping (SPM), a statistical framework and software package. By providing a way to analyse signals measured from the human brain in MRI scanners, SPM triggered the creation of an entirely new field of imaging neuroscience. Beneficiaries include: commercial manufacturers who provide imaging equipment; healthcare practitioners and patients, where SPM is used to deliver new treatments; pharmaceutical industries using SPM to deliver clinical trials; the IT industry developing new software based on SPM; and entirely new industries such as neuromarketing that could only have been created once SPM had been invented.
New computational analysis methods have been developed to make drug discovery and toxicological analysis much more efficient. These methods have been patented (UK, EU, US) and are employed in e-Therapeutics Plc, a computational drug discovery spin-off company of the University. The company, introduced to the Alternative Investment Market of the London Stock Exchange in 2007, is now the eighth largest company (by market capitalisation - £92.7M (26/6/2013)) in the pharma/biotech sector. The underlying technologies derive from network analysis and workflow research at the University. The company has an anti-cancer drug (ETS2101) in phase I clinical trials in the UK and the US, and an anti-depression drug (ETS6103) planned to enter phase IIb clinical trial shortly. The beneficiaries of this research are e- Therapeutics directly, other drug companies, and ultimately patients.
Epilepsy is one of the most common neurological diseases. It is characterised by apparently unpredictable seizures that severely affect the quality of patients' life. In this case study we demonstrate how our research has derived commercial impact within the medical technology industry, as well as impact on researchers and practitioners in neuroscience and medical science. Mathematical research carried out at the Institute of Pure and Applied Mathematics (IPAM) at the University of Aberdeen has led to a threefold impact. First, our research shaped the development, implementation and validation of a new software platform, called EPILAB, containing a vast number of sophisticated algorithms targeting seizure prediction together with novel statistical tools to evaluate prediction performance. Second, our research resulted in commercial impact through the development of a new automatic long term monitoring device, called LTM-EU, by one of our industrial collaborators, Micromed (Italy). Third, a direct consequence of our research is the compilation and commercial exploitation of the world's largest epilepsy database of its type, which enables novel studies into seizure prediction in epilepsy.
Research by Higham, Estrada and Grindrod into new, computable measures for large, dynamically evolving communication networks has allowed the automatic identification of individuals who act as influencers, or efficient listeners. This research insight has been taken up by Bloom Agency (Leeds), a digital marketing and media agency. Bloom has used these ideas to strengthen their Data Insights Team, leading to investment in new jobs, generation of new business and delivery of better results for their clients. Bloom's commercially available real time social planning software product, Whisper, builds directly on the published research, and is at the heart of the agency's success in doubling staff numbers to 60 in recent months, having grown its annual income by 50% to £2.4Million through the use of these new tools.
The Cybernetics team at the University of Reading works at the frontier of human-machine interaction. The group carries out research on therapy and human enhancement in collaboration with medical professionals, to research new therapeutic treatments for patients with paralysis. Our work has led to the first human implantation of BrainGate, an intelligent deep brain stimulator, and the culturing of neurons within a robot body. Our work has been used by neurosurgeons in experimental human trials with the aim to enhance the standard of living of paralysed individuals. This ground breaking, and sometimes controversial work, has sparked widespread discussion and debate in the public sphere, within the media and at the government level, on the use of machines to enhance humans and vice versa.
Researchers in the Centre for the Mathematics of Human Behaviour at the University of Reading have developed a novel approach for the real-time monitoring of evolving social networks. These networks, in which connections between individuals change over time, are an important opportunity for online advertising. The research has been used in collaboration with Bloom Media Ltd to develop a new tool that gives their clients a better understanding of the impacts of social media campaigns. As a result Bloom are leading the field in this area, allowing them to attract major new clients and leading to significant growth of the business. The company now directly employs highly skilled mathematics graduates specifically to work in this area.
This case study provides an account of work on a mathematical framework for the design and optimization of communication networks, and some examples of the framework's influence upon the development of the network congestion control schemes that underlie modern communication networks, notably the Internet.
The impact on protocol development and on network architectures has been significant; in particular on the development of congestion control algorithms and multipath routing algorithms that are stable and fair. Several of the insights on large scale system behaviour have been transferred to help understand cascading failures in other large scale systems, including transport infrastructures.