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Can poly-parameter linear-free energy relationships (pp-LFERs) improve modelling bioaccumulation in fish?

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>01/2018
Number of pages10
Pages (from-to)235-244
Early online date3/10/17
<mark>Original language</mark>English


A wide range of studies have characterized different types of biosorbent, with regards to their interactions with chemicals. This has resulted in the development of poly-parameter linear free energy relationships (pp-LFER) for the estimation of partitioning of neutral organic compounds to biological phases (e.g., storage lipids, phospholipids and serum albumins). The aims of this study were to explore and evaluate the influence of implementing pp-LFERs both into a one-compartment fish model and a multi-compartment physiologically based toxicokinetic (PBTK) fish model and the associated implications for chemical risk assessment. For this purpose, fish was used as reference biota, due to their important role in aquatic food chains and dietary exposure to humans. The bioconcentration factor (BCF) was utilized as the evaluation metric. Overall, our results indicated that models incorporating pp-LFERs (R2 = 0.75) slightly outperformed the single parameter (sp) LFERs approach in the one-compartmental fish model (R2 = 0.72). A pronounced enhancement was achieved for compounds with log KOW between 4 and 5 with increased R2 from 0.52 to 0.71. The little improvement was caused by the overestimation of lipid contribution and underestimation of protein contribution by sp-approach, which cancel each other out. Meanwhile, a greater improvement was observed for multi-compartmental PBTK models with consideration of metabolism, making all predictions fall within a factor of 10 compared with measured data. For screening purposes, the KOW-based (sp-LFERs) approach should be sufficient to quantify the main partitioning characteristics. Further developments are required for the consideration of ionization and more accurate quantification of biotransformation in biota.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Chemosphere. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Chemosphere, 191, 2017 DOI: 10.1016/j.chemosphere.2017.10.007