<?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/6AB06439-37DB-4B8D-93D1-31C197C77012" ns1:id="6AB06439-37DB-4B8D-93D1-31C197C77012"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/B5D887B3-69C3-443A-AF5B-EC4C416DE600" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1E67759A-5E29-4E61-BC84-5B1B8A57F93F" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1E67759A-5E29-4E61-BC84-5B1B8A57F93F" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2026-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/434ECED6-F443-4C5C-AE58-F22725AE163E" ns1:rel="FUND" ns1:start="2024-02-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10089281</ns2:identifier></ns2:identifiers><ns2:title>Presymptom: development of a novel machine-learning-derived diagnostic test to rule out infection to enable enhanced clinical care and better targeted anti-microbial use</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Presymptom Health, a UK-based start-up, is pioneering a portfolio of novel, universal, low-cost diagnostic tests and associated interpretive software algorithms to rule out the presence of infection/sepsis in symptomatic patients.

Presymptom has developed a prototype version of a simple blood test and associated prototype interpretive software to rule out infection from whole blood in post-operative inflamed SIRS (Systemic Inflammatory Response Syndrome) patients. Results can be used to delay or eliminate the use of antibiotics in such SIRS patients who present with symptoms suggestive of potential infection but who in reality have no infection, allowing such patients to be managed instead on a more appropriate care pathway. This will in turn reduce the spread of Antimicrobial Resistance (AMR) and lead to better patient outcomes.

Presymptom's product will comprise a simple blood test to assess host gene expression and associated interpretive software to gauge risk of infection in SIRS patients. The test will run on ubiquitous clinical instrumentation, specifically platforms commonly used within clinical testing labs for routine quantitative RT-PCR based diagnostics, including the many new such instruments deployed since the COVID pandemic. Presymptom's technology platform was discovered based on application of machine learning to a unique fully-annotated presymptomatic database owned by the UK Defence Science &amp;amp; Technologies Laboratory (Dstl).

Current diagnostic approaches to assess infection status include:

* **Observations**: Temperature/Resp. rate/heart-rate/urine output/blood pressure/O2 saturation/appearance/rash. In general, these lack specificty and lead to overuse of antimicrobials.
* **Blood markers**: also lack specificity, CRP, PCT, lactate, urea &amp;amp; electrolytes, glucose, creatine, blood gas, full blood count
* **Microbiology&amp;amp;Culture**: blood culture (BC) sets (1-3 days to result, low sensitivity &amp;amp; high false positive), swabs from multiple sites, PCR from swabs if appropriate.

The main objective of this project is to develop and validate a rapid novel diagnostic test to rule out the presence of infection in post-operative patients, thereby mitigating AMR, reducing hospital costs and delivering improved patient outcomes.</ns2:abstractText></ns2:project>