13 October 2015
SCI's Membership Affairs Committee
SCI, London, UK
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The growing numbers of people with dementia, Alzheimer's disease in particular, presents challenges not only to older people themselves, and to their families, but also to health services and indeed to economies. Its no wonder therefore that politicians have made this a priority area for development. Yet just as, after many years of under-funding, attention is focussed on neurodegeneration, the first trials of putative disease modification therapeutics have reported negative results and drug development looks increasingly difficult in these diseases. This is a very big problem. Might Big Data provide something of a solution or is it a big, albeit fashionable, distraction?
Some evidence suggests that Big Data – whether derived from biological or from clinical datasets might help progress the search for therapeutic interventions in dementia. Research using informatics as a core component will be described both in the field of molecular biomarkers for clinical trial utility and in turning mechanistic understanding into drug development programmes. Then platforms for dementia research utilising large variable datasets – essentially Big Data platforms – will be described including in drug discovery, the Dementias Platform UK and the Innovative Medicines Initiatives – the European Medical Information Framework and the European Prevention of Alzheimer's Disease programme.
Simon Lovestone is Professor of Translational Neuroscience at Oxford University and also Lead for the NIHR Translational Research Collaboration in Dementia (a network of six Biomedical Research Units and Centres in England focussed on dementia), lead for informatics in the Dementias Platform UK and co-coordinator of the European Medical Information Framework. He has research interests in the regulation of tau phosphorylation, dementia therapeutics and in the search for genetic and other biomarkers of Alzheimer's disease. Underpinning all these studies is the use of informatics - clinical informatics, bioinformatics and the challenges of extracting value from very large variable datasets.
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