Press Release
Jun 24, 2023
Co-authors in PLOS Computational Biology

A lack of access to adequate and high-quality data often frustrates the efforts of researchers and clinicians working in the field of antimicrobial resistance. This includes both genomic data of the relevant microbe(s) of interest and data relating to its susceptibility to antimicrobial compounds. Proprietary requirements notwithstanding, access to insights from such data could feasibly contribute to better outcomes more broadly across geographies and public health contexts.

Whilst data may well be available, a lack of interoperability between datasets can limit the extent to which these data can be used to create such outcomes. Differences in data format, level of contextualisation, ease of reproducibility and poorly specified data sharing criteria contribute individually and in combination to this gap in interoperability across datasets that are generated across different research groups.

This gap could, however, be mitigated with use of principles and strategies that streamline how data is collected, reported and shared, with an eye public health more widely.

A recent paper by Chindelevitch et al (2023) in PLOS Computational Biology, of which Heather from our team is a co-author, highlights 10 strategies to close this interoperability gap, by ensuring that AMR-specific genotypical and phenotypical data can be reported and shared more easily and comprehensively in publications. See what you think. 

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