QSAR models for bioconcentration: Is the increase in the complexity justified by more accurate predictions?

This study compares nine QSAR models for the prediction of BCF on fish: four K_OW based models (Veith, Mackay, Bintein and TGD equations) and five complex models (EPI Suite BCFBAF, VEGA CAESAR, VEGA Meylan, VEGA Read-across and VEGA consensus). The aim is to test if increasing complexity leads to predictions that are more accurate than those based only on K_OW are. To this end, experimental BCF data for 1056 compounds, along with experimental and predicted K_OW values, were collected and used for the comparison. A particular focus has been placed on compounds for which metabolism, elimination and specific interactions with tissues can be hypothesized. VEGA Read-across improved global predictions with respect to the K_OW based models and resulted to be a good approach to take into account metabolism and interactions with tissues. For the other complex models, several drawbacks were highlighted. Finally, for different classes of compounds (i.e. Perfluorinated Compounds, Organophosphorous Compounds, Synthetic Pyrethroids and Polychlorinated Biphenyls) results confirmed the mechanistic interpretation of the processes involved in their bioconcentration.