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Artificial intelligence as the new frontier in chemical risk assessment

The rapid progress of AI impacts various areas of life, including toxicology, and promises a major role for AI in future risk assessments. Toxicology has shifted from a purely empirical science focused on observing chemical exposure outcomes to a data-rich field ripe for AI integration. AI methods a...

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Autor principal: Hartung, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616238/
https://www.ncbi.nlm.nih.gov/pubmed/37915539
http://dx.doi.org/10.3389/frai.2023.1269932
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author Hartung, Thomas
author_facet Hartung, Thomas
author_sort Hartung, Thomas
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description The rapid progress of AI impacts various areas of life, including toxicology, and promises a major role for AI in future risk assessments. Toxicology has shifted from a purely empirical science focused on observing chemical exposure outcomes to a data-rich field ripe for AI integration. AI methods are well-suited to handling and integrating large, diverse data volumes - a key challenge in modern toxicology. Additionally, AI enables Predictive Toxicology, as demonstrated by the automated read-across tool RASAR that achieved 87% balanced accuracy across nine OECD tests and 190,000 chemicals, outperforming animal test reproducibility. AI’s ability to handle big data and provide probabilistic outputs facilitates probabilistic risk assessment. Rather than just replicating human skills at larger scales, AI should be viewed as a transformative technology. Despite potential challenges, like model black-boxing and dataset biases, explainable AI (xAI) is emerging to address these issues.
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spelling pubmed-106162382023-11-01 Artificial intelligence as the new frontier in chemical risk assessment Hartung, Thomas Front Artif Intell Artificial Intelligence The rapid progress of AI impacts various areas of life, including toxicology, and promises a major role for AI in future risk assessments. Toxicology has shifted from a purely empirical science focused on observing chemical exposure outcomes to a data-rich field ripe for AI integration. AI methods are well-suited to handling and integrating large, diverse data volumes - a key challenge in modern toxicology. Additionally, AI enables Predictive Toxicology, as demonstrated by the automated read-across tool RASAR that achieved 87% balanced accuracy across nine OECD tests and 190,000 chemicals, outperforming animal test reproducibility. AI’s ability to handle big data and provide probabilistic outputs facilitates probabilistic risk assessment. Rather than just replicating human skills at larger scales, AI should be viewed as a transformative technology. Despite potential challenges, like model black-boxing and dataset biases, explainable AI (xAI) is emerging to address these issues. Frontiers Media S.A. 2023-10-17 /pmc/articles/PMC10616238/ /pubmed/37915539 http://dx.doi.org/10.3389/frai.2023.1269932 Text en Copyright © 2023 Hartung. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Hartung, Thomas
Artificial intelligence as the new frontier in chemical risk assessment
title Artificial intelligence as the new frontier in chemical risk assessment
title_full Artificial intelligence as the new frontier in chemical risk assessment
title_fullStr Artificial intelligence as the new frontier in chemical risk assessment
title_full_unstemmed Artificial intelligence as the new frontier in chemical risk assessment
title_short Artificial intelligence as the new frontier in chemical risk assessment
title_sort artificial intelligence as the new frontier in chemical risk assessment
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616238/
https://www.ncbi.nlm.nih.gov/pubmed/37915539
http://dx.doi.org/10.3389/frai.2023.1269932
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