<?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/A9FD398B-1980-484F-982F-5460D636E473" ns1:id="A9FD398B-1980-484F-982F-5460D636E473"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/3CB8D2B5-3CD5-4748-B9C8-07AC3A37A732" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DC1F3CD9-6D00-4771-9B8F-A61AD7CD6D86" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DC1F3CD9-6D00-4771-9B8F-A61AD7CD6D86" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/9E4F7C70-9382-472B-974E-59E3B455FF92" ns1:rel="FUND" ns1:start="2024-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10096804</ns2:identifier></ns2:identifiers><ns2:title>Archer: Next-generation unstructured data access for hospitals and clinical trial sponsors, delivering efficiency, reducing costs and improving care</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>IgniteData is an innovative, UK-based SME with a goal to transform the interoperability of healthcare provider (Electronic Health Record (EHR)) and clinical trial sponsor (Electronic Data Capture (EDC)) systems through its Software-as-a-Service platform **Archer**.

**Project Objectives/Summary**

The first generation of Archer has been successfully developed and deployed to transfer structured data (e.g. patient records in EHR systems) from an EHR to an EDC. However, **up to 85% of actionable health data is stored in unstructured formats** (e.g. clinical narrative text found in Pathology reports, Radiology reports, Postoperative notes).

This project will create the second-generation of Archer through the development of an AI-/NLP-driven module which answers trial-relevant questions from unstructured EHR data and inputs results into EDCs.

**Market Opportunity/Need**

The valuable data stored in unstructured formats within EHRs is currently resource-intensive and challenging to extract. Manual data transfer and reviews are still commonplace, despite being often time-consuming, slow-to-turnaround and error-prone since medical conditions and supporting evidence can potentially be missed \[Wong, 2016\]. Source-Document-Verification (required by manual data transfer to avoid errors) can alone account for 10-15% trial costs (e.g. ~&amp;pound;1-1.5m/PII trial).

**Impacts/Project Outputs**

* Directly extracting unstructured information from EHRs will enable exceptional reductions in the costs currently associated with on-site monitoring/auditing.
* Second-generation Archer platform will deliver transformative growth within 5-years of launch.</ns2:abstractText></ns2:project>