Rare Daily Staff

A $521,819 (£400,000) grant will help fund a project to help with the identification, diagnosis, and treatment of people in the United Kingdom who have a rare disease.

The Rare Diseases Sprint Exemplar Innovation Project aims to develop a secure, cloud-research platform with the potential to transform the understanding of rare genetic disorders, drive improvements in diagnosis, and provide proof of principle for use in other diseases.

The project hopes to help patients and the UK’s National Health Service save money. The cost of an undiagnosed rare disease patient is more than twice that of other patients, an average difference of $9,000 more per patient per year.

The aim is to build on advances in clinical imaging, pathology, and genomic technologies in understanding rare diseases by creating a secure, anonymized platform to draw together and integrate data from the NHS with research data.

The project will initially involve patients with rare diseases recruited to the National Institute for Health Research’s BioResource for Translational Research in Common and Rare Diseases—a database of volunteers who have already provided consent that information retrieved from their health records can be used for medical research.

The project will be funded by UK Research and Innovation and is a collaboration between Cambridge University Health Partners and Eastern Academic Health Science Network, which will be working with NHS Trusts, and the National Disease Registries at Public Health England, Microsoft Research, and the Wellcome Sanger Institute to build on the NIHR investment in the NIHR BioResource.

“Rare diseases can be extremely difficult to diagnose because they often have an unidentified genetic cause,” says John Bradley, director NIHR Cambridge Biomedical Research Centre and co-chair of NIHR BioResource. “Recent advances in clinical imaging, pathology, and genomic technologies have led to remarkable progress in understanding disease – particularly rare diseases, but the power of these technologies cannot be fully realized until the immense volume of data generated can be integrated with NHS data, then analyzed. This is what our project aims to achieve.”

 

February 4, 2019
Photo: John Bradley, Co-Chair of NIHR BioResource

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