<?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/665288EB-1CAF-42C6-BD59-512C155699AF" ns1:id="665288EB-1CAF-42C6-BD59-512C155699AF"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/876A0C48-4D7B-448A-B20B-8F851657AEDA" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/54C06099-EB51-4C7A-AEE2-3A1C4B902697" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/80345FE1-52E7-4194-B9BA-95C482D409A3" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C367CD74-4B6B-4665-B6BE-E70775DFEDDD" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/4F562EF2-2966-414A-ABD6-A0CBB0FE3B32" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/54C06099-EB51-4C7A-AEE2-3A1C4B902697" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-10-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/75231891-2397-4969-8578-8803F5B92B62" ns1:rel="FUND" ns1:start="2022-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10027358</ns2:identifier></ns2:identifiers><ns2:title>Predicting kidney and liver damage in cancer patients receiving chemotherapy</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Chemotherapy is the treatment of disease using chemical substances, commonly used to treat cancer.

Chemotherapy is often cytotoxic and two common risks relate to kidney and liver damage. Affected patients may require delays or changes to treatment and even treatment suspension.

Whilst only &amp;lt;10% of patients will encounter kidney and or liver damage, current best practice requires monitoring for all patients with regular blood testing. There is currently no way to stratify risk in individual patients.

**The vision for this project is to accurately predict the risk of kidney and liver damage in patients receiving chemotherapy**. The result of this prediction will mean low risk patients can be saved unnecessary trips to hospital for blood tests and monitoring whilst high risk patients can receive more appropriate management.

To date, computer scientists at Durham University, working closely with pharmacists at University College London Hospital (UCLH) have developed a machine learning algorithm to accurately predict liver and kidney function.

Results have been shared at a number of key conferences and stakeholder events and there is strong clinical interest in utilising this algorithm in clinical practice.

**The main area of focus for this project will be a prospective diagnostic accuracy study**. This will produce a commercial proof-of-concept (POC) software application that will allow the validated algorithm, produced by Durham University academics, to be used in live clinical practice.

Key objectives will include:

* Develop POC software to allow algorithm to be tested in a live clinical setting

* Rapid iterative development of POC to enable commercial launch

* Data collection to validation algorithm

* Identification of third-party software interface opportunities (particularly chemotherapy e-prescribing systems)

* Development of commercialisation plan

Currently ~375k patients are diagnosed with cancer every year in the UK, with ~28% of these expected to receive chemotherapy for their primary disease[[1]][0].

With similar rates of cancer incidence across the Western world, this innovation could personalise care for millions globally.

 
https://www.cancerresearchuk.org/health-professional/cancer-statistics/incidence

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