Antimicrobial resistance (AMR) is a major challenge in our globalised world, and tackling it will take the combined resources and effort of researchers working across different disciplines. Technical advances in recent years continue to expand our ability to collect vast amounts of genomic information on pathogens, and a wealth of data is being collected in epidemiological and surveillance studies, including on the socio-economic burden of AMR.

Our 4th conference in this series will bring together basic researchers, clinicians, computer scientists, and policymakers interested in pathogen genomics, epidemiology, surveillance, and machine learning to explore the recent advances and current challenges of the field.

This year’s programme will once again focus on genomic evidence and how to implement it in clinical practice and policy for AMR control. The meeting will highlight the advances in machine learning, AI and computational tools to predict AMR. We will also discuss how to build an international genomics infrastructure to tackle AMR and emerging lessons from other global public health issues.

This conference will be a hybrid meeting – with onsite or virtual attendance. In addition to invited talks, the programme will include short oral presentations selected from abstracts, posters, poster pitches and networking breaks for further discussion.