From big data to smart decisions: artificial intelligence in kidney risk assessment.

[en] Artificial intelligence approaches that link patient data with chemical-induced kidney injury patterns are revolutionizing nephrotoxicity risk assessment. Substantial progress has been made in the development of integrated approaches that leverage big data, molecular profiles and toxicological understanding to identify at-risk patients, provide insights into molecular mechanisms and advance predictive nephrology.

Disciplines :

Life sciences: Multidisciplinary, general & others

Author, co-author :

Barnes, Devon A; Utrecht University, Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht, Netherlands

Maia Ladeira, Luiz Carlos ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Génie biomécanique

Masereeuw, Rosalinde ; Utrecht University, Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht, Netherlands. r.masereeuw@uu.nl

Language :

English

Title :

From big data to smart decisions: artificial intelligence in kidney risk assessment.

Publication date :

07 April 2025

Journal title :

Nature Reviews Nephrology

ISSN :

1759-5061

eISSN :

1759-507X

Publisher :

Nature, England

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.nature.com/articles/s41581-025-00962-1.pdf

European Projects :

H2020 - 963845 - ONTOX - Ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment

Funders :

EU - European Union
NWO - Netherlands Organisation for Scientific Research

Funding text :

The authors work was performed in the context of the ONTOX project ( https://ontox-project.eu/ ), which has received funding from the European Union Horizon 2020 Research and Innovation programme under grant agreement no. 963845, as well as the Virtual Human Platform for Safety Assessment (VHP4Safety) project, funded by the Netherlands Research Council (NWO) Netherlands Research Agenda: Research on Routes by Consortia (NWA-ORC 1292.19.272). ONTOX is part of the ASPIS project cluster ( https://aspis-cluster.eu/ ).

Available on ORBi :

since 28 April 2025

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Bibliography

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