<?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/6A40990A-20A0-4D55-91BA-B83DAB013A03" ns1:id="6A40990A-20A0-4D55-91BA-B83DAB013A03"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/238DED96-1ED2-4697-BC14-33D8B65A095A" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/934182C8-7368-4C66-B24B-6DAC2090A0C1" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/934182C8-7368-4C66-B24B-6DAC2090A0C1" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/2EBCC169-13F8-4E3A-B92F-95BE8AC88DF6" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2027-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/B52A4687-B936-4145-B5EB-2CCA332A85A7" ns1:rel="FUND" ns1:start="2025-02-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10141831</ns2:identifier></ns2:identifiers><ns2:title>ZeroShotAPI: Using ZeroShot Machine Learning and an automated HTE reactor to derive universal chemical reaction condition parameters for Active Pharmaceutical Ingredients.</ns2:title><ns2:status>Active</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>This project aims to develops a software platform combining sophisticated Machine Learning approaches and proprietary data from a High Throughput Experimentation reactor to derive universal chemical reaction condition parameters to optimise the sustainable manufacturing of Active Pharmaceutical Ingredients.</ns2:abstractText></ns2:project>