A new study by the Newcastle University and Chinese Academy of Sciences, co-led by Professor David W Graham and Professor Yong-Guan Zhu, compiled a comprehensive database of 254,738 articles spanning two decades to examine global AMR research patterns.
The study revealed significant differences in terminology and methods used across medical, veterinary, food safety, plant agriculture, and environmental sectors. These semantic and methodological disparities lead to limited cross-sectoral valuation and communication, causing inconsistent messages to decision-makers.
Using sophisticated AI analysis, the team created global maps of AMR research activities, highlighting a stark lack of interdisciplinary collaboration, especially in low-income countries where the burden of AMR is greatest.
Commenting on the study, Professor David W Graham said, “Our paper’s findings support key messages from UN Environment Programme and World Health Organization that emphasise the best way to mitigate AMR is through prevention and integrated surveillance, which is key to prioritising solutions.”
Published in the journal Environment International, the findings underscore why One Health-based solutions to AMR are not developing as needed. The results aim to guide better integration of AMR surveillance across various sectors and regions worldwide.
Mitigating AMR
Professor David W Graham, Emeritus Professor of Engineering at Newcastle University, said: “The findings highlight the urgent need for greater coordination in research methods across sectors and regions. For instance, the medical and veterinary communities need information about living AMR infectious pathogens to prioritise decisions, whereas environmental researchers often focus on genetic targets. Our work shows that culturing microbiology and isolate sequencing, and metagenomics must be performed in tandem in all future work, and more context data must be collected to relate results from different sectors. Our paper’s findings support key messages from UN Environment Programme and World Health Organization that emphasise the best way to mitigate AMR is through prevention and integrated surveillance, which is key to prioritising solutions.”
This issue is being addressed by the United Nations Quadripartite Technical Group on Integrated Surveillance on Antimicrobial Use and Resistance, which includes both Professor Zhu and Professor Graham as members.
Graham further said, “This work was only possible due to its novel use of Artificial Intelligence and Natural Language Processing to intelligently search an extensive and living database, an archive we make openly available for public use and contributions. This paper represents the first in a series of joint manuscripts leveraging AI to guide future AMR and other research agenda.”
Professor Yong-Guan Zhu, Professor of Environmental Sciences, the Chinese Academy of Sciences, added: “The framework of One Health is of critical importance in safeguarding human and ecosystem health, but it needs roadmaps to implement, this study timely identifies a path forward. The study also demonstrates that multidisciplinary and international collaboration is essential in solving global challenges, and we should embrace emerging technologies, such as AI”.
Both scientists advocate for future research and increased investment in capacity building, particularly in low-income countries, to tackle the urgent AMR challenges in these regions.
Funding: This research is financially supported by the National Natural Science Foundation of China and the Ningbo Municipality.
