<?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/4210CF41-7A53-4E9E-BBC5-E8852C631966" ns1:id="4210CF41-7A53-4E9E-BBC5-E8852C631966"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/84103E95-9055-4E77-8327-8EA595F9404F" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/7303B5C4-ED14-4E51-935A-2D66F4625705" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/7303B5C4-ED14-4E51-935A-2D66F4625705" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2027-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/29A4502C-7BBE-40F4-B2F8-E929A46B2E21" ns1:rel="FUND" ns1:start="2025-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10142894</ns2:identifier></ns2:identifiers><ns2:title>AI-guided antibiotic discovery for urinary tract infections</ns2:title><ns2:status>Active</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Urinary tract infections (UTIs) are among the most common bacterial infections, impacting 50-60% of women during their lifetimes. UTIs are also the UK's leading infection in healthcare settings and responsible for 18,000 life-threatening bloodstream infections each year. ?70% of UTIs are caused by _E. coli_: a WHO critical priority bacterial pathogen associated with multidrug resistance. Uncomplicated UTIs are typically treated with oral antibiotics prescribed by a GP, but spreading antimicrobial resistance means these drugs are increasingly failing, leaving doctors with fewer treatment options. Spreading resistance also causes the emergence of multidrug-resistant species, which are difficult to treat and are linked with 800,000 deaths each year. Left unchecked, antimicrobial drug resistance could cause an estimated 10 million deaths by 2050 - more than cancer and diabetes combined. With no novel oral antibiotics against UTIs in the last 20 years, there is an urgent need for new drugs to ensure that UTIs and other _E. coli_ infections remain treatable. 70% of all clinically-used antibiotics derive from the ~1% of soil microbes that can be cultured in the laboratory using standard techniques. Culturable microbes have now been exhausted for novel antibiotics whilst efforts to discover new synthetic solutions have failed to fill the gap and have proven costly to develop (?&amp;pound;1Bn per novel antibiotic).

Accessing the remaining 99% of uncultured microbes represents the best opportunity to discover new antibiotics. Bactobio's proprietary platform integrates bio-engineering, next-generation sequencing, and machine learning to cultivate previously unculturable microbes. Our library uniquely contains ?1,700 novel species, representing 10% of bacterial species ever cultured.

In this project, we will create a step-change in our platform's efficiency by incorporating proprietary machine learning, automation, and data capture. We will then apply our enhanced platform to expand and screen our in-house library of novel microbes for production of novel antibiotics against _E. coli_. We have set an ambitious goal of finding 3-5 promising antibiotic lead compounds, with an aim to elicit strong licensing interest (recent licensing deals were priced at ?&amp;pound;60Mn per compound). Outputs from this project would provide real hope for a new treatment against UTIs and other _E. coli_ infections. More broadly, this project will provide a boost to the UK's growing life sciences sector and re-establish the antibiotic discovery pipeline.</ns2:abstractText></ns2:project>