Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies.
Exposure
Study design
Toxicokinetics
Weight of evidence
Journal
Regulatory toxicology and pharmacology : RTP
ISSN: 1096-0295
Titre abrégé: Regul Toxicol Pharmacol
Pays: Netherlands
ID NLM: 8214983
Informations de publication
Date de publication:
Dec 2021
Dec 2021
Historique:
received:
16
08
2021
revised:
23
10
2021
accepted:
27
10
2021
pubmed:
9
11
2021
medline:
20
1
2022
entrez:
8
11
2021
Statut:
ppublish
Résumé
Human health risks from chronic exposures to environmental chemicals are typically estimated from potential human exposure estimates and dose-response data obtained from repeated-dose animal toxicity studies. Various criteria are available for selecting the top (highest) dose used in these animal studies. For example, toxicokinetic (TK) and toxicological data provided by shorter-term or dose range finding studies can be evaluated in a weight of evidence approach to provide insight into the dose range that would provide dose-response data that are relevant to human exposures. However, there are concerns that a top dose resulting from the consideration of TK data may be too low compared to other criteria, such as the limit dose or the maximum tolerated dose. In this paper, we address several concerns related to human exposures by discussing 1) the resources and methods available to predict human exposure levels and the associated uncertainty and variability, and 2) the margin between predicted human exposure levels and the dose levels used in repeated-dose animal studies. A series of case studies, ranging from data-rich to data-poor chemicals, are presented to demonstrate that expected human exposures to environmental chemicals are typically orders of magnitude lower than no-observed-adverse-effect levels/lowest-observed-adverse-effect levels (NOAELs/LOAELs) when available (used as conservative surrogates for top doses). The results of these case studies support that a top dose based, in part, on TK data is typically orders of magnitude higher than expected human exposure levels.
Identifiants
pubmed: 34743952
pii: S0273-2300(21)00214-2
doi: 10.1016/j.yrtph.2021.105073
pmc: PMC8767482
mid: NIHMS1767894
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
105073Subventions
Organisme : Intramural EPA
ID : EPA999999
Pays : United States
Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.
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