By integrating previously overlooked drivers AI boosts bioaccumulation assessment in fish
The increasing use of chemicals has led to the integration of the bioconcentration factor (BCF) into chemical regulation. A machine learning model trained on chemical properties and test conditions for 962 chemicals enabled us to estimate experimental BCFs in 16 fish species with up to 90 % accuracy. We showed that the BCF is not, as generally assumed, a fixed chemical-specific criterion, but increases with lower exposure concentration and longer exposure duration. A review of 165 regulatory studies submitted to EU authorities showed that about half of the chemicals that should have been classified as bioaccumulative according to worst-case criteria defined in our study were not so classified based on the experimental BCFs submitted. We therefore propose the implementation of two new objective metrics, BCF50 for minimum requirement bioaccumulation screening and BCF90 as a realistic worst-case surrogate, into regulation.
Authors
- Ines Prutz
- Reza Aalizadeh (ORCID: https://orcid.org/0000-0001-9167-9060)
- Peter C. von der Ohe (ORCID: https://orcid.org/0000-0001-7350-8962)
- Thomas Gräff (ORCID: https://orcid.org/0000-0003-1164-586X)
- Rita Triebskorn (ORCID: https://orcid.org/0000-0002-7446-4997)
- Νikolaos S. Τhomaidis (ORCID: https://orcid.org/0000-0002-4624-4735)
- Katharina Peschke
- Heinz‐R. Köhler
- Gabriele Treu (ORCID: https://orcid.org/0000-0002-9277-1835)
Institutions
- National and Kapodistrian University of Athens (GR)
- Steinbeis Foundation (DE)
- German Environment Agency (DE)
- University of Tübingen (DE)
Publication Details
- Journal
- Journal of Hazardous Materials
- Published
- 2025-11-29
- DOI
- https://doi.org/10.1016/j.jhazmat.2025.140648
- Primary Topic
- Environmental Toxicology and Ecotoxicology
- Type
- article
- Field-Weighted Citation Impact
- 0.00