29 June 2023
The Royal Free London has been awarded almost £4 million of funding from the National Institute for Health and Care Research (NIHR) as part of a national investment in clinical research infrastructure.
The money will be used to buy a range of state-of-the-art equipment to expand the research capacity of pharmacy, develop our clinical research laboratory and invest in new technologies including a dedicated research MRI scanner.
The opportunity to compete for this funding was a consequence of the successful application for NIHR Clinical Research Facility (CRF) funding last year.
Professor Tim Meyer, CRF director and lead applicant, said: “This award represents another significant investment by NIHR in clinical research at the Royal Free London. Greater capacity within the pharmacy means we can support more innovative trials including gene and cell therapy, for which the trust has a leading reputation. This investment will also allow us to purchase state-of the-art equipment to develop our laboratory which will process and analyse samples from our expanding portfolio of clinical studies.”
Farhan Naim, director of research and development at the Royal Free London, added: "This additional NIHR funding will provide a welcome boost to the clinical research infrastructure at RFL. The broad range of equipment that it will fund will go a long way in ensuring that we are able to realise our vision of offering optimal clinical research access to our local patient populations and staff."
Dan Knight, consultant cardiologist, said: “The new low-field MRI scanner will support our ground-breaking research into interventional MRI, which we believe will significantly improve patient outcomes. This investment will also open up entirely new areas of imaging research in the unique patient populations served by the Royal Free Hospital such as those with pulmonary hypertension, connective tissue disease and interstitial lung disease. It will also further strengthen our existing collaborations with UCL researchers in the fields of translational imaging, engineering and machine learning.”