Inclusion of soil arsenic bioaccessibility in ecological risk assessment and comparison with biological effects

An in vitro method for determining the bioaccessibility of pharmaceuticals in wildlife

Wildlife can be exposed to human pharmaceuticals via prey that have accumulated the compounds from wastewater, surface water, sediment, and soil. One factor affecting internal absorption of pharmaceuticals is bioaccessibility, the proportion of the compound that enters solution in the gastrointestinal tract. Currently, the bioaccessibility of most pharmaceuticals in prey remains unknown for most wildlife species. The authors evaluated the potential of a 2-compartment in vitro gastrointestinal tract model to compare the bioaccessibility of the antidepressant fluoxetine from invertebrate prey for birds and mammals. Samples of gizzard (or stomach) and intestinal-phase digestive juices were obtained from the in vitro models along with the residual solid material. High-performance liquid chromatographic analysis revealed that the bioaccessibility of fluoxetine in the avian in vitro models was statistically significantly lower than that in the mammalian models as a percentage of what was recovered; however, there were no statistically or biologically significant interspecies difference in terms of the amount recovered per gram of "food" inserted at the start of the simulation. This in vitro model provides a useful method of comparing the bioaccessibility of pharmaceuticals in different prey for species with different gastrointestinal conditions. There is merit for ecological risk assessments in further developing this in vitro approach to improve estimates of internal exposure for organics. Environ Toxicol Chem 2016;35:2349-2357. © 2016 SETAC.

Using sparse dose-response data for wildlife risk assessment

Hazard quotients based on a point-estimate comparison of exposure to a toxicity reference value (TRV) are commonly used to characterize risks for wildlife. Quotients may be appropriate for screening-level assessments but should be avoided in detailed assessments, because they provide little insight regarding the likely magnitude of effects and associated uncertainty. To better characterize risks to wildlife and support more informed decision making, practitioners should make full use of available dose-response data. First, relevant studies should be compiled and data extracted. Data extractions are not trivial--practitioners must evaluate the potential use of each study or its components, extract numerous variables, and in some cases, calculate variables of interest. Second, plots should be used to thoroughly explore the data, especially in the range of doses relevant to a given risk assessment. Plots should be used to understand variation in dose-response among studies, species, and other factors. Finally, quantitative dose-response models should be considered if they are likely to provide an improved basis for decision making. The most common dose-response models are simple models for data from a particular study for a particular species, using generalized linear models or other models appropriate for a given endpoint. Although simple models work well in some instances, they generally do not reflect the full breadth of information in a dose-response data set, because they apply only for particular studies, species, and endpoints. More advanced models are available that explicitly account for variation among studies and species, or that standardize multiple endpoints to a common response variable. Application of these models may be useful in some cases when data are abundant, but there are challenges to implementing and interpreting such models when data are sparse.