A Novel Multispecies Toxicokinetic Modeling Approach in Support of Chemical Risk Assessment.

Area of Science:

• Environmental toxicology
• Ecotoxicology
• Computational toxicology

Background:

• Standardized chemical risk assessments rely on limited model species, failing to capture full biodiversity.
• Existing multispecies models are constrained by the availability of single-species data.
• Ethical and practical limitations hinder testing chemicals across numerous species.

Purpose of the Study:

• To develop a "bottom-up" multispecies physiologically based toxicokinetic (PBTK) model for predicting chemical bioconcentration.
• To utilize data from 69 Canadian freshwater fish species to parameterize the model.
• To assess the model's accuracy in predicting bioconcentration factors (BCFs) for various chemicals.

Main Methods:

• Developed a "bottom-up" PBTK model integrating data from 69 freshwater fish species.
• Employed Monte Carlo-like simulations with statistical parameter distributions.
• Predicted steady-state bioconcentration factors (BCFs) for selected chemicals.

Main Results:

• Predicted BCFs for 1,4-dichlorobenzene and dichlorodiphenyltrichloroethane showed good overlap with empirical data.
• The model tended to slightly overestimate measured BCFs.
• For 82% of 34 tested chemicals, predicted BCFs deviated less than 10-fold from measured values.

Conclusions:

• The "bottom-up" multispecies PBTK model offers environmentally relevant bioconcentration predictions.
• This approach enhances chemical risk assessment by accounting for species diversity.
• Model accuracy is comparable to existing single-species models.