About the Project
EMBARQ's primary purpose is to provide a knowledge base and develop innovative tools for quantifying the impact of these organisms, facilitating rapid assessment methods for industry and regulators.
The project proposes four novel aspects for risk assessment: tracking biologicals in the environment, calibrating risks against natural fluctuations, integrating AI tools for risk assessment, and considering a OneHealth perspective.
EMBARQ will expand traditional risk assessment steps to cover various risk factors, e.g how horizontal gene transfer may affect pathogenicity, and assess environmental impacts.
News & Resources
Unraveling Horizontal Gene Transfer and Ecosystem Impacts of Biopesticides
EMBARQ is often looking for good new recruits, however right now no positions are being advertized.
EMBARQ will build a risk assessment framework to support safety, sustainability, and biodiversity.
Approach
EMBARQ researchers at Aarhus and Copenhagen universities will track biologicals and microbial behaviour
EMBARQ will develop a one health based hazard assessment at the Statens Serum Institute in Copenhagen
Environmental hazard assessment will be expanded to European scales using AI driven tools at Aalborg University Denmark
Planning
EMBARQ will gather relevant data on factors such as horizontal gene transfer or key microbes.
EMBARQ will use methods such as metagenomics to investigate effects of perturbation and large scale variation.
EMBARQ will investigate geographic and climatic variation using AI and bioinformatic big data.
EMBARQ will investigate bioprotection and bioremediation with meta-genomics, transcriptomics and metabolomics.
EMBARQ will develop recommendations based on research findings to support safer and more sustainable practices.
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Our Team
Pioneering soil microbial ecology and horizontal gene transfer in the environment.
Environmental risk analysis, RNA analysis, in vivo impact testing
Human risk analyses, Exposure analysis, national reference, diagnostics, typing methods
AI tool development, data analysis, high performance computing
Contact
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The work presented in this publication is supported by Novo Nordisk Foundation grant NNF23400085294