UKRI
Data Platform for the National PET Imaging Platform (NPIP)
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The Data Platform for the National PET Imaging Platform (NPIP) is a UKRI-funded consortium infrastructure project supporting the development of a data management and analytics system for the UK's coordinated PET imaging network. This call is open to UK-based research institutions and industry partners collaborating to build interoperable data infrastructure for nuclear medicine imaging research and clinical translation.
Details
| Funder | UKRI |
| Consortium | Required |
| Eligible countries | GB |
Who Should Apply
- •UK research institutions with PET imaging facilities or nuclear medicine expertise
- •Industry partners offering data management, informatics or software solutions
- •Consortia combining academic, NHS and commercial stakeholders
- •Teams with experience in multi-site data harmonisation and imaging informatics
Key Dates
- •Call first listed 22 March 2026 (verify exact deadline on UKRI portal)
Tips for Applicants
- ✓Consortium structure is mandatory; clarity on roles, data-sharing agreements and governance between partners is essential.
- ✓Demonstrate interoperability with existing NHS imaging infrastructure and national data standards.
- ✓Address sustainability and long-term operational funding; UKRI panels assess whether the platform can function beyond the grant period.
Frequently Asked Questions
Is the NPIP Data Platform call open to single institutions?
No, a consortium is required; applications must include multiple organisations with defined roles and collaboration agreements.
Can non-UK partners join the NPIP Data Platform consortium?
The call is restricted to GB-eligible institutions; verify co-investigator eligibility on the UKRI portal, as some schemes allow international partners in supporting roles.
What kind of data infrastructure does NPIP fund?
The Data Platform supports systems for collecting, storing, harmonising and analysing PET imaging data across multiple UK centres to enable research translation and clinical application.
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Summary generated by AI based on published grant information. Always verify details on the funder's website.
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