Cargando…
An approach for mixture testing and prioritization based on common kinetic groups
In light of an ever-increasing exposure to chemicals, the topic of potential mixture toxicity has gained increased attention, particularly as the toxicological toolbox to address such questions has vastly improved. Routinely toxicological risk assessments will rely on the analysis of individual comp...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9095521/ https://www.ncbi.nlm.nih.gov/pubmed/35306572 http://dx.doi.org/10.1007/s00204-022-03264-8 |
_version_ | 1784705771444895744 |
---|---|
author | Braeuning, Albert Bloch, Denise Karaca, Mawien Kneuer, Carsten Rotter, Stefanie Tralau, Tewes Marx-Stoelting, Philip |
author_facet | Braeuning, Albert Bloch, Denise Karaca, Mawien Kneuer, Carsten Rotter, Stefanie Tralau, Tewes Marx-Stoelting, Philip |
author_sort | Braeuning, Albert |
collection | PubMed |
description | In light of an ever-increasing exposure to chemicals, the topic of potential mixture toxicity has gained increased attention, particularly as the toxicological toolbox to address such questions has vastly improved. Routinely toxicological risk assessments will rely on the analysis of individual compounds with mixture effects being considered only in those specific cases where co-exposure is foreseeable, for example for pesticides or food contact materials. In the field of pesticides, active substances are summarized in so-called cumulative assessment groups (CAG) which are primarily based on their toxicodynamic properties, that is, respective target organs and mode of action (MoA). In this context, compounds causing toxicity by a similar MoA are assumed to follow a model of dose/concentration addition (DACA). However, the respective approach inherently falls short of addressing cases where there are dissimilar or independent MoAs resulting in wider toxicokinetic effects. Yet, the latter are often the underlying cause when effects deviate from the DACA model. In the present manuscript, we therefore suggest additionally to consider toxicokinetic effects (especially related to xenobiotic metabolism and transporter interaction) for the grouping of substances to predict mixture toxicity. In line with the concept of MoA-based CAGs, we propose common kinetics groups (CKGs) as an additional tool for grouping of chemicals and mixture prioritization. Fundamentals of the CKG concept are discussed, along with challenges for its implementation, and methodological approaches and examples are explored. |
format | Online Article Text |
id | pubmed-9095521 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-90955212022-05-13 An approach for mixture testing and prioritization based on common kinetic groups Braeuning, Albert Bloch, Denise Karaca, Mawien Kneuer, Carsten Rotter, Stefanie Tralau, Tewes Marx-Stoelting, Philip Arch Toxicol Regulatory Toxicology In light of an ever-increasing exposure to chemicals, the topic of potential mixture toxicity has gained increased attention, particularly as the toxicological toolbox to address such questions has vastly improved. Routinely toxicological risk assessments will rely on the analysis of individual compounds with mixture effects being considered only in those specific cases where co-exposure is foreseeable, for example for pesticides or food contact materials. In the field of pesticides, active substances are summarized in so-called cumulative assessment groups (CAG) which are primarily based on their toxicodynamic properties, that is, respective target organs and mode of action (MoA). In this context, compounds causing toxicity by a similar MoA are assumed to follow a model of dose/concentration addition (DACA). However, the respective approach inherently falls short of addressing cases where there are dissimilar or independent MoAs resulting in wider toxicokinetic effects. Yet, the latter are often the underlying cause when effects deviate from the DACA model. In the present manuscript, we therefore suggest additionally to consider toxicokinetic effects (especially related to xenobiotic metabolism and transporter interaction) for the grouping of substances to predict mixture toxicity. In line with the concept of MoA-based CAGs, we propose common kinetics groups (CKGs) as an additional tool for grouping of chemicals and mixture prioritization. Fundamentals of the CKG concept are discussed, along with challenges for its implementation, and methodological approaches and examples are explored. Springer Berlin Heidelberg 2022-03-19 2022 /pmc/articles/PMC9095521/ /pubmed/35306572 http://dx.doi.org/10.1007/s00204-022-03264-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Regulatory Toxicology Braeuning, Albert Bloch, Denise Karaca, Mawien Kneuer, Carsten Rotter, Stefanie Tralau, Tewes Marx-Stoelting, Philip An approach for mixture testing and prioritization based on common kinetic groups |
title | An approach for mixture testing and prioritization based on common kinetic groups |
title_full | An approach for mixture testing and prioritization based on common kinetic groups |
title_fullStr | An approach for mixture testing and prioritization based on common kinetic groups |
title_full_unstemmed | An approach for mixture testing and prioritization based on common kinetic groups |
title_short | An approach for mixture testing and prioritization based on common kinetic groups |
title_sort | approach for mixture testing and prioritization based on common kinetic groups |
topic | Regulatory Toxicology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9095521/ https://www.ncbi.nlm.nih.gov/pubmed/35306572 http://dx.doi.org/10.1007/s00204-022-03264-8 |
work_keys_str_mv | AT braeuningalbert anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT blochdenise anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT karacamawien anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT kneuercarsten anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT rotterstefanie anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT tralautewes anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT marxstoeltingphilip anapproachformixturetestingandprioritizationbasedoncommonkineticgroups AT braeuningalbert approachformixturetestingandprioritizationbasedoncommonkineticgroups AT blochdenise approachformixturetestingandprioritizationbasedoncommonkineticgroups AT karacamawien approachformixturetestingandprioritizationbasedoncommonkineticgroups AT kneuercarsten approachformixturetestingandprioritizationbasedoncommonkineticgroups AT rotterstefanie approachformixturetestingandprioritizationbasedoncommonkineticgroups AT tralautewes approachformixturetestingandprioritizationbasedoncommonkineticgroups AT marxstoeltingphilip approachformixturetestingandprioritizationbasedoncommonkineticgroups |