<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/BE3C5EDE-67FE-490B-A6A6-371EB765C3BB" ns1:id="BE3C5EDE-67FE-490B-A6A6-371EB765C3BB"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/C4527F95-947B-4CB5-BD32-BC6248D5A9F1" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/640BF1C4-A0F5-480A-B9A8-A14AD6F29E48" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/362276FA-9E5A-44ED-B712-530B69176157" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/640BF1C4-A0F5-480A-B9A8-A14AD6F29E48" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-07-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/839A86D7-14F1-48BE-976D-AE32DC36F069" ns1:rel="FUND" ns1:start="2017-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">103859</ns2:identifier></ns2:identifiers><ns2:title>Automated Cancer Prognosis and Diagnosis Using MultiColoured Luminspheres™</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The project will develop and validate a method for automatically analysing cellular patterns, labelled by immunohistochemistry. Currently, pathologists visually assess tissue samples in order to diagnose diseases such as cancer and provide a prognosis. Currently a maximum of three biomarkers can be analysed at one time. Analysing multiple biomarkers provides a more detailed picture of disease status and progression and enables physicians to provide personalised and more effective treatments. The method that will be developed and validated through this project will facilitate the analysis of multiple biomarkers in a shortened space of time by using innovative software to complete the analysis. Initial testing has shown the method to be successful. Further development through this project will result in a method which has been validated for the prognosis and diagnosis of cancer. The success of the project will enable a reduction in the economic cost of disease, eliminating human subjectivity, enabling rigorous cross-validation to minimise the chance of identifying erroneous patterns via more precise diagnosis and treatment selection, better patient outcome, and improved service efficiency via automation.</ns2:abstractText></ns2:project>