Antimicrobial resistance has become 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 huge amounts of genomic information on pathogens and their hosts, and a wealth of data is being collected in epidemiological and surveillance studies, including on the socio-economic burden of AMR. With a quantum leap in computer science, researchers have also started to explore novel technological approaches such as machine learning to analyse and predict AMR
, together with modelling of the global burden from drug-resistant infection.
To help facilitate this cross-discipline interaction and tool development, we would like to invite basic researchers, computer scientists, clinicians and policy makers interested in pathogen and human/host genomics, machine learning, development of novel diagnostic tools and translation of AMR-data into clinical practice, to join us for this new conference.

This meeting will highlight the importance of Big Data and genomics in the fight against AMR. It will showcase recent advances in the rapidly emerging field of machine learning to predict AMR, approaches to monitor and evaluate the global burden of disease, novel technologies for the diagnosis of drug-resistant infections, and the use of pathogen genomics to address critical questions relating to surveillance, epidemiology, transmission and treatment of drug-resistant infections.

We welcome abstracts from all areas relevant to the main themes of the meeting, for both oral and poster presentations. Several oral presentations will be chosen from the abstracts submitted.

Early Bird Deadline:
4 September 2018

Bursary Deadline:
18 September 2018

Abstract Deadline:
2 October 2018

Registration Deadline:
30 October 2018

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(or call us: +44 (0)1223 495100
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