<?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="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/FCF86130-CC06-4C98-8EE3-7C945BE67179" ns1:id="FCF86130-CC06-4C98-8EE3-7C945BE67179"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/9C7ECD4C-80D1-4842-97B9-CCB2FB7D9BD3" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D6286810-8ED4-42BC-BE37-29DE3921CA78" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C1FF0EAE-A2FD-4E96-A7CF-58458F07B7F1" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D6286810-8ED4-42BC-BE37-29DE3921CA78" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-08-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/EBEACF0E-212A-4907-98F8-0B3011BF5C30" ns1:rel="FUND" ns1:start="2021-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">89370</ns2:identifier></ns2:identifiers><ns2:title>Glioblastoma Multiforme Patient Stratification through Novel integration of Artificial Intelligence, Big Data and Phenotypic Screening</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Glamorous AI, a UK SME, is pioneering cutting-edge ML methods for drug and biomarker discovery. In collaboration with leading researchers from King's College London, the team aims to run a comprehensive study on GBM patients derived cell lines to deliver novel predictive biomarkers that enable efficient stratification strategies and reduce cost of treatment.</ns2:abstractText></ns2:project>