Toxicokinetic Triage for Environmental Chemicals

Area of Science:

• Environmental toxicology and computational chemistry.
• Development and validation of predictive toxicokinetic (TK) models.

Background:

• Toxicokinetic (TK) models are crucial for linking chemical doses to concentrations in biological systems.
• High-throughput TK (HTTK) models enable rapid in vitro to in vivo extrapolation using chemical properties.
• A key application is 'reverse dosimetry,' converting in vitro bioactive concentrations to in vivo doses.

Purpose of the Study:

• To evaluate the accuracy of approximations and assumptions in HTTK reverse dosimetry.
• To develop criteria for determining the suitability of HTTK tools for specific chemicals.
• To propose a framework for prioritizing chemicals lacking TK data.

Main Methods:

• Analysis of literature in vivo data for 87 chemicals to identify predictors of poor HTTK performance.
• Development of a generic high-throughput physiologically based TK (HTPBTK) model for 271 chemicals.
• Evaluation of reverse dosimetry assumptions using the HTPBTK model, particularly for bioaccumulative compounds.
• Proposal of a 4-element framework for chemical TK triage, categorizing chemicals into 7 groups.

Main Results:

• Specific chemical properties (in vitro HTTK data, physicochemical descriptors, predicted transporter affinities) were correlated with poor HTTK predictive ability.
• HTTK reverse dosimetry assumptions were generally appropriate, with notable exceptions for highly bioaccumulative substances.
• The HTPBTK model successfully predicted chemical concentration time-courses for various exposure scenarios.
• A TK triage framework was proposed to guide the application of HTTK for chemicals with limited data.

Conclusions:

• HTTK models are valuable tools, but their applicability requires careful assessment based on chemical-specific properties.
• The study provides methods to identify chemicals where HTTK may lead to false conclusions, particularly highly bioaccumulative ones.
• The proposed TK triage framework aids in prioritizing and managing chemicals with unknown toxicokinetic profiles.