<?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="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/F33C692F-3BBE-4C34-80F4-80B9617F6D51" ns1:id="F33C692F-3BBE-4C34-80F4-80B9617F6D51"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/2ED090B4-37B5-483E-ADE2-30EA57785745" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9754E6F0-A8EE-4C46-B548-11974C4F487A" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9754E6F0-A8EE-4C46-B548-11974C4F487A" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2026-07-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/9B294877-5CF4-457B-98C9-3EBBC0495D30" ns1:rel="FUND" ns1:start="2024-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10123755</ns2:identifier></ns2:identifiers><ns2:title>BR[AI]N...it's a no-brainer: First in Class Artificial Intelligence (AI) Enabled Digital Biomarker for Dementia Risk Prediction and Characterisation</ns2:title><ns2:status>Active</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Despite the rapidly increasing numbers of people living with dementia, there are substantial difficulties with diagnosis. Around a third of people living with dementia have not received a diagnosis. Even in people who are diagnosed, there is typically a delay of years between developing symptoms and receiving a diagnosis. These problems mean that people are not empowered by receiving information about what is causing their symptoms and are unable to access treatments. The first treatment that has shown promise in slowing down the progression of dementia has just been approved for use in the USA, making a timely and accurate diagnosis of dementia an urgent priority.

One important reason for delayed and inaccurate dementia diagnosis is that the human eye is not reliably able to tell from brain scans who has early dementia and who is likely to experience deterioration in their memory in the future. We propose using artificial intelligence to derive this information from routine brain scans.

AINOSTICS' technology represents a breakthrough that would provide an automated and personalized healthcare platform for assisting in the clinical diagnosis of dementia using multi-modal imaging and non-imaging data that are already routinely acquired in healthcare and research settings. This technology is useful for both the treatment of patients and, importantly, the development of novel therapeutics and biomarkers.

AINOSTICS' technology can automatically and intelligently analyze scans to provide sensitive and accurate micro-structural information about key tissue and organ structures, and then compare this with information from healthy populations to detect the signatures of the disease. We intend for AINOSTICS' software to become a routine part of clinical practice and drug development as the results of our intelligent analysis will provide clinicians, researchers, and imaging centres with a convenient and cost-effective means to obtain reliable, quantitative, and objective diagnostic and prognostic data.

For serious global diseases, AINOSTICS' technology has the potential to save time during patient assessments, accelerate clinical pathways, standardise the quality of care, and improve patient outcomes, in addition to making important contributions to the development of disease-modifying therapeutics.</ns2:abstractText></ns2:project>