Predictive framework for estimating exposure of birds to pharmaceuticals
Thomas G Bean1, Kathryn E Arnold1, Julie M Lane2
1Environment Department, University of York, York, United Kingdom.
This study introduces a framework to estimate pharmaceutical levels in wildlife near wastewater treatment plants (WWTPs). Rodent data improved predictions, but tissue distribution accuracy needs further research for ecological risk assessments.
Area of Science:
- Environmental Toxicology
- Ecotoxicology
- Pharmacokinetics in Wildlife
Background:
- Pharmaceuticals are increasingly detected in aquatic environments.
- Wildlife feeding at wastewater treatment plants (WWTPs) face potential exposure.
- Limited pharmacokinetic data for wildlife hinders ecological risk assessment.
Purpose of the Study:
- To develop and evaluate a predictive framework for estimating pharmaceutical concentrations in wildlife.
- To assess the accumulation and uptake of pharmaceuticals in wildlife food chains.
- To determine the effectiveness of a read-across approach using human or rodent data for wildlife pharmacokinetics.
Main Methods:
- A multi-step framework estimating pharmaceutical concentrations in wastewater, food items, and wildlife tissues.
- Utilizing a read-across approach with rodent and human pharmacokinetic data (absorption, distribution, metabolism, excretion).
- Comparing framework predictions against experimental data for birds exposed to fluoxetine at WWTPs.
Main Results:
- Estimated wastewater concentrations were lower than measured.
- Food concentrations were reasonably estimated with bioaccumulation data.
- Rodent-to-bird read-across performed better than human-to-bird.
- The framework adequately predicted plasma concentrations and elimination but poorly predicted tissue distribution.
Conclusions:
- The developed framework shows promise for estimating pharmaceutical exposure in wildlife.
- Improving understanding of physiological differences between birds and mammals is crucial for accurate risk assessment.
- Further research is needed to refine tissue distribution predictions in ecological risk assessments.
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