A weight-of-evidence approach for the bioaccumulation assessment of triclosan in aquatic species.

The bioaccumulation assessment of chemicals is challenging because of various metrics and criteria, multiple lines of evidence and underlying uncertainty in the data. Measured in vivo laboratory and field bioaccumulation data are generally considered preferable; however, quantitative structure-activity relationships (QSARs), mass balance models and in vitro data can also be considered. This case study critically evaluates in vivo, in vitro and in silico data and provides new data for the bioaccumulation assessment of triclosan (TCS). The review focusses on measured fish bioconcentration factors (BCFs) because this is the most commonly used regulatory metric. Reported measured fish BCFs range from about 20 to 8700L/kg-ww spanning a range of possible bioaccumulation assessment outcomes, i.e. from "not bioaccumulative" to "very bioaccumulative". Estimated biotransformation rate constants for fish obtained from in vivo, in vitro and in silico methods show general consensus fostering confidence in the selection of plausible values to confront uncertainty in the measured fish BCF tests. Other measurements (lines of evidence) from various species are also collected and reviewed. The estimated biotransformation rate constants and selected chemical property data are used to parameterize bioaccumulation models for aquatic species. Collectively the available lines of evidence are presented using a weight of evidence approach for assessing the bioaccumulation of TCS in aquatic species. Acceptable quality measured data and model predictions for TCS BCFs and bioaccumulation factors are lower than 2000L/kg. Biomagnification factors are <1 (kg/kg). The general consistency in the acceptable quality data is largely explained by the relatively efficient rates of TCS biotransformation in a range of species including measurements of significant in vitro activity of phase II conjugation reactions. The review demonstrates the value of combining models and measurements and, when necessary, applying multiple lines of evidence for chemical assessment.