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

Area of Science:

• Pharmacokinetics and Toxicological Risk Assessment
• Environmental Health Sciences
• Computational Toxicology

Background:

• External chemical concentrations are commonly used for exposure assessment, but internal concentrations better predict toxicological responses.
• Absorption, Distribution, Metabolism, and Excretion (ADME) processes link external to internal concentrations, often exhibiting saturation at high doses.
• Saturation can lead to nonlinear internal dose-response relationships, complicating risk assessment.

Purpose of the Study:

• To explore how saturable ADME processes influence the internal to external concentration (IEC) relationship using physiologically-based pharmacokinetic (PBPK) models.
• To investigate the impact of kinetic parameters, exposure routes, frequency, and duration on IEC relationships for various chemicals and species.
• To demonstrate PBPK modeling as an alternative to traditional statistical methods for analyzing dose proportionality in chemical safety assessments.

Main Methods:

• Development and application of generic PBPK models to simulate hypothetical chemical exposures.
• Utilized PBPK models for styrene and caffeine to examine effects of exposure scenarios in rats and humans.
• Analyzed 2,4-dichlorophenoxyacetic acid plasma concentration data using a PBPK modeling approach.

Main Results:

• Differences in kinetic parameters significantly alter the shape of the IEC relationship.
• Exposure route, frequency, and duration demonstrably impact IEC relationships for styrene and caffeine.
• PBPK modeling effectively analyzed dose proportionality for 2,4-dichlorophenoxyacetic acid, offering an alternative to statistical methods.

Conclusions:

• PBPK models are valuable tools for understanding the complex relationship between external and internal chemical exposures.
• This approach can reveal nonlinear dose-response behaviors arising from saturable ADME processes.
• PBPK modeling aids in optimizing toxicity study designs and interpreting results for robust chemical safety assessments.