<?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/C0DA6EE4-9588-40B3-8138-6D2A9E69093B" ns1:id="C0DA6EE4-9588-40B3-8138-6D2A9E69093B"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/265B19AF-9091-4266-9506-3304D4AA9071" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/EA97E663-6EB0-418D-8132-E1F732FFFC61" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/EA97E663-6EB0-418D-8132-E1F732FFFC61" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-12-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/60FDA2D0-02F5-4B5D-B7C6-54A64398E3DF" ns1:rel="FUND" ns1:start="2018-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">104592</ns2:identifier></ns2:identifiers><ns2:title>Development of the Mendelian Rare Disease Screening Platform - for the fast, accurate, automated diagnosis of rare disease</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>&amp;quot;**VISION:** The diagnosis of rare disease is complex, challenging and costly - with missed and misdiagnosis having a significant health and economic consequences for both patients and the NHS. We intend to redress this and make diagnosis easy, quick and most importantly accurate - overcoming some the key technical and clinical issues associated with the current diagnosis process.

**OBJECTIVES**: Building on our prototype rare disease database, which suggests rare disease diagnosis with 78% accuracy based upon the input of of 5 defined symptoms, we want to develop the world's first automated rare disease screening tool.

Designed to sit alongside and integrate directly with medical record software at a GP clinic or hospital, utilizing SnoMed code classifiers, the tool is capable of automatically scanning patient's medical record for symptoms, past and present, and then cross referencing these against our live database of 8000+ rare diseases, flagging potential, undiagnosed rare disease patients. These are then ranked in order to give a weighting, enabling a doctor to make an informed decision regarding likelihood, need and urgency of treatment. Many of these hard to diagnose diseases have effective treatments that can drastically improve patient outcomes and reduce costs and burden on medical systems.

**FOCUS:** The project focuses on the development of four key elements;

1. Integration into electronic health systems through API and with SnoMed code classifiers.
2. Development of the patient screening system which will plug onto the current Mendelian diagnosis suggestion tool
3. Working with selected specialist physicians and clinical experts to determine the patterns, weighting and recommendations for each disease group as well as the health economics behind these.
4. Development of the personalised alert system

**INNOVATION**: The first real-time patient screening tool that will flag potential undiagnosed rare disease patients within health systems.

**OUTCOME**: There are over 3 million rare disease patients in the UK (350m+ worldwide) making this a sizeable commercial opportunity, as well as directly addressing a defined UK NHS and global need. The benefits of this are sizable and immediate;

* Patients: Quicker access to the correct treatment, improving health impacts and enable preventative treatments through earlier diagnosis.
* Clinicians: Reduce diagnosis time;, reduce misdiagnosis; reducing research needed for diagnosis and number of appointment.
* NHS: Potentially save NHS &amp;pound;2.6bn per year in rare disease cost (&amp;pound;15bn NHS spending X 25% diagnosis spend x 70% saving).&amp;quot;</ns2:abstractText></ns2:project>