Human Apparent Volume of Distribution Predicts Bioaccumulation of Ionizable Organic Chemicals in Zebrafish Embryos

Chemicals with elevated bioaccumulation profiles present potential hazards to public health and the environment. Ionizable organic compounds (IOCs) increasingly represent a large proportion of commercial chemicals; however, historical approaches for bioaccumulation determinations are mainly developed for neutral chemicals, which were not appropriate for IOCs. Herein, we employed the zebrafish embryo, a common vertebrate model in environmental and biomedical studies, to elucidate toxicokinetics and bioconcentration of eight IOCs with diverse physicochemical properties and pharmacokinetic parameters. At an environmentally relevant pH (7.5), most IOCs exhibited rapid uptake and depuration in zebrafish, suggesting the ionized forms of IOCs are readily bioavailable. Bioconcentration factors (BCF) of these IOCs ranged from 0.0530 to 250 L.kg(-1) wet weight. The human pharmacokinetic proportionality factor, apparent volume of distribution (VD), better predicted the BCF of selected IOCs than more commonly used hydrophobicity-based parameters (e.g., pH-dependent octanol-water distribution ratio, Dow). Predictive bioaccumulation models for IOCs were constructed and validated using VD alone or with Dow. Significant relationships between fish BCF and human VD, which is readily available for pharmaceuticals, highlighted the utility of biologically based read-across approaches for predicting bioaccumulative potential of IOCs. Our novel findings thus provided an understanding of the partitioning behavior and improved predictive bioconcentration modeling for IOCs.

Automated summary

Chemicals with elevated bioaccumulation profiles pose potential risks to public health and the environment. Existing methods for bioaccumulation determination are not suitable for ionizable organic compounds (IOCs). By using the zebrafish embryo model, researchers elucidated the toxicokinetics and bioconcentration of eight IOCs with diverse traits. The results provide an understanding of the partitioning behavior of IOCs and improve predictive bioconcentration modeling.