📣: In partnership with the David Braley Centre for Antibiotic Discovery, we are proud to announce the recipients of our 2024 Undergraduate Student Fellowships. These awards provide funding for undergrads to work in IIDR labs over the summer practicum. Meet this year's cohort! 👇
Autumn Arnold has trained an ensemble of machine learning models to predict the antibacterial activity of over 12 million molecules, of which nine have shown potent antibacterial activity against priority pathogens. This summer, Autumn will study the most promising among them.
Mei Chiao will build upon an existing antibiotic resistance platform at McMaster. This research will improve accessibility and reduce rediscovery, thereby streamlining protocols and strategies in the fight against antibiotic resistance.
Emily D'Agostini will investigate the role of probiotics in counteracting overrepresentation of adherent-invasive E. coli in the gut. This work has implications for the treatment and management of inflammatory bowel diseases, like Crohn's disease.
Paankhi Dave will study interactions between phage and pilus proteins — research that may inform new strategies to combat bacterial infections.
Anna Fan will conduct AI-guided drug discovery research in hopes of identifying a compound that can safely and effectively inhibit a particularly fatal Salmonella Typhimurium sequence type.
Esther Jeong will study cell expansion and isolation techniques to increase availability and utility of humanized mice in studies related to HIV and tuberculosis.
Tiffany Ta will use machine learning and natural language processing tasks to extract terms from nearly 35,000 AMR-related scientific publications available on PubMed Central.
Wesley Ta will use machine learning approaches to predict novelly synergistic pairs of existing, approved medicines. This research is designed to identify new treatment candidates for drug-resistant gram-negative bacteria, like Klebsiella pneumoniae and Acinetobacter baumannii.
Jennifer Tindall will study strains of adherent-invasive E. coli in host-mimicking conditions to determine the factors that influence the bacteria's ability to colonize hosts.