<?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/911084CF-EA1A-4AD9-8180-5DBC8CE61F3A" ns1:id="911084CF-EA1A-4AD9-8180-5DBC8CE61F3A"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/8C97BBF9-4879-444D-818B-63411BD53276" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B7157A5F-3C90-41D4-9E64-B43756739568" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B7157A5F-3C90-41D4-9E64-B43756739568" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-06-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/BEC162B7-57CF-44B6-8A4E-F5EC7AD824D2" ns1:rel="FUND" ns1:start="2025-01-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10146367</ns2:identifier></ns2:identifiers><ns2:title>Streamlining the use of biocatalysis for API manufacture through digitisation, AI and machine learning</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Biocatalysis offers a sustainable method for medicines manufacturing yet requires expert domain knowledge for it to be considered during synthesis route planning or optimisation. Digital tools for planning and evaluating chemo-biocatalytic routes would have a huge impact in supporting scientists planning sustainable manufacturing routes, by providing the expert knowledge and highlighting where enzymatic steps offer significant economic and environmental benefits. Furthermore, by integrating machine learning models for biocatalytic reaction feasibility into digital retrosynthetic planning, we can de-risk the use of enzymes so that they can be considered with confidence. Finally, linking these tools directly with enzyme manufacturers will allow the right enzymes to be seamlessly purchased and evaluated for sustainable manufacturing of essential medicines, further lowering the barrier-to-entry for biocatalysis.

Developing the right digital tools to tackle these challenges requires collaboration with stakeholders across the supply chain. In this initial expression of interest project, we will bring together ideas and expertise from the pharmaceutical industry, academia, enzyme manufactures, and those working in regulation and standards, to identify how digitisation, AI and machine learning could steamline the use of biocatalysis and its potential for sustainable medicines manufacture. Through interviews and workshops, we will further build up a picture of the opportunity in this space, producing an open access market landscape report, and a consortium to take on this grand challenge in the next phase.</ns2:abstractText></ns2:project>