AMR_ML-Boost-Focus

Antimicrobial resistance poses a growing challenge to the effective treatment of serious bacterial infections. In time-critical situations, clinicians often initiate broad-spectrum therapy while awaiting laboratory susceptibility results, a practice that can compromise patient outcomes and accelerate the development of resistance.

This project seeks to make better use of routinely collected antimicrobial testing data to support earlier, more informed treatment decisions. By examining patterns of bacterial response across multiple antibiotics within standard laboratory workflows, the research aims to identify early indicators of effective therapy without introducing new assays or altering clinical practice.

By enabling more timely and targeted treatment, this work has the potential to improve patient outcomes, reduce unnecessary exposure to broad-spectrum antibiotics, and strengthen antimicrobial stewardship. At the population level, aggregated phenotypic response data can complement existing surveillance efforts, while the reliance on routine laboratory data supports scalable, cost-effective integration into healthcare systems.