Creating a network of digital pathology, imaging and AI centres

Fund Name: Creating a network of digital pathology, imaging and AI centres
Project Length: TBA
Project Value: Share of £50M
Deadline: 01/08/2018

Up to £50 million is available to establish centres of excellence in digital pathology and/or medical imaging with artificial intelligence (AI).

Summary

As part of the delivery of the Industrial Strategy Challenge Fund (ISCF) in data to early diagnosis and precision medicine, Innovate UK, as part of UK Research and Innovation will invest up to £50 million. This is to establish a network of 5 to 6 centres of excellence, across the UK, in digital pathology and/or medical imaging, including radiology. The centres must use digital systems and artificial intelligence (AI) to improve diagnosis and deliver precision treatments.

As radiology and medical imaging is already digitised, bids in this area should look for significant added value from digital systems, enhanced analytics and AI. Applicants may wish to consider the design, development, evaluation and adoption of clinical decision support systems – evaluating, for example, new patient care pathways and providing clinicians with improved tools that will support precision medicine. These elements can also form part of a digital pathology bid (especially in combination with radiology/imaging).

Eligibility

To be eligible for funding you must be:

  • an NHS Trust (or equivalent in the Devolved Administrations)
  • NHS England, NHS Scotland, NHS Wales or Health and Social Care Northern Ireland
  • a hospital
  • an Academic Health Science Network (AHSN)
  • a university or other research organisation
  • a charity
  • a UK based business of any size
  • carry out your programme work in the UK
  • intend to exploit the results for the benefit of the UK

Programmes must be collaborative and at least 2 collaborators must apply for grant.

Get in Touch

If you think that you might be eligible for this fund, please Get In Touch by filling out the contact form below.

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