University Research Lecturer
My research focusses on mitigating antimicrobial resistance, with a current focus on tuberculosis.
1. Improve the quality of phenotype measurements collected by the international TB consortium, CRyPTIC. This project is tests the antibiotic susceptibility of >25,000 clinical strains collected worldwide using a commercial 96-well microtitre plate. In addition to the measurements carried out in the partner laboratories, a photo of each plate is read by some software, AMyGDA, that I developed. I also run BashTheBug which is a Citizen Science project that invites anyone to help us classify especially difficult images. The large dataset collected by CRyPTIC will not only enable the construction of a more accurate tuberculosis resistance catalogue but also will open up new, interesting avenues of AMR research.
2. Develop de novo methods that can predict the effect of protein mutations on a specific antibiotic. I approach this problem from a protein structure perspective; to date we have applied molecular simulation and machine learning methods to predict AMR.
(2023), European Respiratory Journal, 61, 2300426 - 2300426
Brankin AE. and Fowler PW., (2023), JAC Antimicrob Resist, 5
Brunner V. and Fowler P., (2023)
(2022), European Respiratory Journal, 60, 2200239 - 2200239
Brankin AE. and Fowler PW., (2022), Journal of Computational Chemistry