Data Challange: Before the Breakpoint

Antimicrobial resistance (AMR) occurs when bacteria become less responsive to antibiotics, making infections harder to treat and increasing the risk of prolonged illness, complications, and death. AMR also raises treatment costs and puts pressure on already stretched health systems. Most AMR surveillance currently focuses on whether bacteria are classified as “susceptible” or “resistant” using laboratory breakpoints. While useful, this approach may miss earlier warning signs that resistance is beginning to develop.
In the laboratory we use measurements called minimum inhibitory concentrations (MICs) to assess how well antibiotics work against bacteria; our proposed research will examine whether subtle changes in MICs can detect a hidden “pre-resistance” stage before full resistance becomes apparent. Using large international AMR surveillance datasets, we will analyze how MIC patterns change over time across different countries, bacterial species, and antibiotics. The aim is to develop an early-warning framework that can identify concerning shifts sooner than standard resistance summaries alone.
This research could improve patient outcomes by helping clinicians and health systems recognize when commonly used antibiotics are “just-starting” to lose effectiveness before treatment failure becomes more widespread. Earlier detection will support more timely updates to treatment guidance, reduce ineffective antibiotic use, and improve the chances that patients receive medicines that are still likely to work.
It could strengthen antimicrobial stewardship by allowing programs to act earlier, review prescribing practices, and protect the effectiveness of existing antibiotics rather than waiting until resistance levels are already high. It could also inform public health practice by providing a more sensitive way to interpret surveillance data, identify emerging AMR threats, and prioritize monitoring and response efforts. Finally, it could strengthen health systems by improving how laboratories, surveillance programs, and policymakers use routine AMR data to support preparedness, better decision-making, and more efficient use of limited resources.