Vice-Chancellor’s Catalyst Award
The Vice-Chancellor’s Catalyst Award provides early career researchers with an opportunity to develop their leadership skills as a researcher and position themselves as competitive for external funding.
We seek to fund high-quality research projects relevant to LSTM research strategic priorities.
The fund supports specific new projects. Priority is given to pump-priming or pilot projects, which, it is hoped, will generate preliminary data that can attract further funding opportunities for the individual from external sources once completed.
Funding may be used to fund a piece of exploratory research, testing of new interventions, the cultivation of new research links, small-scale experiments or field work, development of prototypes, etc.
2026 award winners
Dr Frank Tianyi
Clinical Outcomes and Biomarker Research in Africa (COBRA): a pilot study on neurotoxic envenoming.
Project summary
Each year, neurotoxic snakebite kills thousands of people in sub-Saharan Africa, yet no validated bedside tool exists to objectively grade severity or guide antivenom dosing.
This project, conducted at a specialist snakebite centre in Guinea, will be the first to validate the Iowa Oral Performance Instrument (IOPI), a simple tongue-pressure device, as a severity measure for neurotoxic envenoming.
Alongside this, serial blood samples from envenomed patients will be used to identify and validate plasma biomarkers for earlier diagnosis, using a three-stage mass spectrometry pipeline.
Together, these outputs will provide the methodological infrastructure needed for future clinical trials of snakebite treatments in West Africa.
View Frank’s research profile
Dr Richard Goodman
Applying AI to antimicrobial drug discovery: Predicting novel antimicrobial activity directly from bacterial genomes using supervised machine learning.
Project summary
Antimicrobial resistance is a major global health crisis, yet discovering new antibiotics with traditional approaches is incredibly slow.
Nature remains our best source for these medicines and LSTM holds a vast library of 78,636 environmental microbes.
I will train an AI model on 2,000 of these microbes which have genomes matched with antimicrobial profiles, to produce a model which predicts if a microbe produces new antibiotics simply by scanning its DNA.
This proof-of-concept AI model will provide the foundation for a larger, multi-industry bio-discovery platform, transforming how we find antibiotics, insecticide compounds and affordable therapeutics in the future.
View Richard’s research profileDr Rachel Owen
Elucidating the molecular mechanisms underlying zoonotic persistence and spillover of filoviruses from bat reservoirs using replication competent virus-like particles
Project summary
Bats represent a significant environmental reservoir of zoonotic viruses which cause serious human disease, including the filoviruses which cause Ebola and Marburg virus-associated disease.
Despite the risk these viruses pose to human health, relatively little is known about the molecular factors influencing zoonotic spillover events and determinants of infection.
This is largely due to these viruses requiring high containment to study. This project will develop virus-like particles, which resemble viral structures, and minigenomes that mimic viral genomes to study how filoviruses infect and replicate in bat cells compared to human cells, and to investigate how bat-derived sequences impact cell entry.
View Rachel’s research profile