Base-line model for identifying the bioaccumulation potential of chemicals

TLDR

The baseline model assumes a maximum bioconcentration factor (BCF) that is reduced by mitigating factors, with the maximum potential described by a multi‑compartment partitioning model for passive diffusion. The study investigates the relative importance of mitigating factors affecting bioconcentration, such as organism interactions and bioavailability. The model incorporates a fish‑liver simulator trained on mammalian metabolic pathways and accounts for chemical properties such as size and ionization, and its predictability was tested on 176 chemicals not used in training. Metabolism emerged as the most important mitigating factor, and the model achieved an r² of 0.84 on a training set of 511 chemicals, with 80 % prediction accuracy (|log BSF Obs − log BCF Calc| ≤ 0.75) for 59 chemicals within its applicability domain.

Abstract

The base-line modeling concept presented in this work is based on the assumption of a maximum bioconcentration factor (BCF ) with mitigating factors that reduce the BCF. The maximum bioconcentration potential was described by the multi-compartment partitioning model for passive diffusion. The significance of different mitigating factors associated either with interactions with an organism or bioavailability were investigated. The most important mitigating factor was found to be metabolism. Accordingly, a simulator for fish liver was used in the model, which has been trained to reproduce fish metabolism based on related mammalian metabolic pathways. Other significant mitigating factors, depending on the chemical structure, e.g. molecular size and ionization were also taken into account in the model. The results (r 2 = 0.84) obtained for a training set of 511 chemicals demonstrate the usefulness of the BCF base line concept. The predictability of the model was evaluated on the basis of 176 chemicals not used in the model building. The correctness of predictions (abs(log BSF Obs − log BCF Calc) ≤ 0.75)) for 59 chemicals included within the model applicability domain was 80%.