Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling.

Animal Study Design Internal Concentrations Nonlinear Pharmacokinetics Physiologically Based Pharmacokinetic (PBPK) Saturation of Absorption Saturation of Clearance

Journal

Toxicology and applied pharmacology
ISSN: 1096-0333
Titre abrégé: Toxicol Appl Pharmacol
Pays: United States
ID NLM: 0416575

Informations de publication

Date de publication:
01 04 2022
Historique:
received: 08 12 2021
revised: 19 01 2022
accepted: 10 02 2022
pubmed: 18 2 2022
medline: 30 4 2022
entrez: 17 2 2022
Statut: ppublish

Résumé

Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.

Identifiants

pubmed: 35176293
pii: S0041-008X(22)00067-9
doi: 10.1016/j.taap.2022.115922
pmc: PMC10519136
mid: NIHMS1930677
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

115922

Subventions

Organisme : Intramural EPA
ID : EPA999999
Pays : United States

Informations de copyright

Published by Elsevier Inc.

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Auteurs

Daniel Hoer (D)

U.S. Environmental Protection Agency, Office of Pesticide Programs, Durham, NC, USA.

Hugh A Barton (HA)

Consultant, Mystic, CT, USA.

Alicia Paini (A)

European Commission, Joint Research Centre, Ispra, Italy. Electronic address: alicia.paini@esqlabs.com.

Michael Bartels (M)

ToxMetrics.com, LLC, Midland, MI, USA.

Brandall Ingle (B)

U.S. Environmental Protection Agency, Office of Pesticide Programs, Durham, NC, USA.

Jeanne Domoradzki (J)

Corteva Agriscience, Indianapolis, IN, USA.

Jeffrey Fisher (J)

ScitoVation, Durham, NC, USA.

Michelle Embry (M)

Health and Environmental Sciences Institute, Washington, DC, USA.

Philip Villanueva (P)

U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA.

David Miller (D)

U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA.

James Nguyen (J)

U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA.

Qiang Zhang (Q)

Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

Stephen W Edwards (SW)

RTI International, Research Triangle Park, NC, USA.

Yu-Mei Tan (YM)

U.S. Environmental Protection Agency, Office of Pesticide Programs, Durham, NC, USA. Electronic address: tan.cecilia@epa.gov.

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Classifications MeSH