MICA: Medical Bioinformatics: Data-Driven Discovery for Personalised Medicine

点击翻译按钮获取中文摘要

We will improve patient health and medical research by maximising the use of vast amounts of human data being generated in the NHS. But there are two obstacles: (i) inter-related clinical and research datasets are dispersed across numerous computer systems making them hard to integrate; (ii) there is a serious shortage of computational expertise as applied to clinical research. As part of the UK's healthcare strategy to overcome these limitations, we have assembled a world-class consortium of institutions and scientists, including UCL Partners (containing NHS Trusts treating >6 million patients), Francis Crick Institute, Sanger Institute and European Bioinformatics Institute. Close links with the NHS (through Farr and Genomics England) will allow information exchange for health and disease progression. We have also engaged leading companies like GSK and Intel.We will use the MRC funds for two purposes:1. Create a powerful eMedLab data centre. We will build a computer cluster that allows us to store, integrate and analyse genetic, patient and electronic health records. By co-locating in a single centre, we eliminate delays and security risks that occur when information is transmitted. Research Technologists supplied by the partners will install and maintain the infrastructure and software environment. 2. Expand scientific and technical expertise in UK Medical Bioinformatics through a Research & Training Academy. Basic and clinical scientists, and bioinformaticians will be trained to perform world-leading computational biomedical science. We will train in the whole range of skills involved in medical bioinformatics research with taught courses, seminars, workshops and informal discussion. To coordinate research activities across partners, we will establish Academy Labs, which are flexible, semi-overlapping groupings of academic and industrial researchers to share insights and plan activities in areas of common analytical challenges. The Academy will provide a mechanism for information and skills exchange across the traditional boundaries of disease types.These will enable existing projects in 3 disease domains in which we have unique strengths: rare diseases, cardiovascular diseases and cancer. Rare: We house 31/70 Nationally Commissioned Highly Specialised Services; ~0.5M of the 6M of our patients have a rare disease, including >50% of those treated at Great Ormond Street Hospital. >200 research teams generate large quantities of genetic, imaging (eg, 3D facial reconstructions), and clinical information (eg, patient records). Cardiovascular: We also lead genomic, imaging, and health informatics programmes in cardiovascular disease with contributions to projects like UK10k project and host multiple national cardiovascular registries through the National Institute for Cardiovascular Outcomes Research. These are linked to primary and hospital clinical care records through Farr@UCLP with current cohort sizes of ~2M people. Cancer: We also have particular clinical expertise in some of the most difficult to treat cancer types and we host major international data resources. These include individuals recruited to the TRACERx study of lung cancer, 8,500 women with abnormal cervical smears in whom methylation patterns of the HPV16 genome predict progression to high-grade precursor disease, and one of the largest sarcoma biobanks in the world. Ultimately, this bid will allow us to use new computational approaches to (i) link patient records and research data in order to understand the pathogenesis of disease, (ii) use genomic, imaging and clinical data to identify diagnostic, prognostic and predictive biomarkers to guide therapy, predict outcome and increase recruitment to clinical trials based on stratified populations and (iii) translate new IP by engagement with the pharmaceutical industry.