Using the fish plasma model to prioritize pharmaceuticals and protect fish from potential adverse effects

In the absence of a robust database of adverse effects to aquatic biota from pharmaceuticals introduced into the environment, alternate approaches are needed to assess risk. One such approach is the fish plasma model (FPM), which can be used to prioritize pharmaceuticals as a function of potential altered biological responses for fish exposed to these chemicals in receiving waters. Other published prioritization schemes assessing effects utilize quantitative-structure activity relationships, cellular assays, biochemical markers, and various apical effects. The FPM provides another line of evidence that is complementary to these approaches. We also examined potential effects due to human Ether-à-go-go-Related Gene activity for the active pharmaceutical ingredients (APIs) as another potentially useful and complementary approach for prioritization. In this study, we used the FPM to examine predicted effects for the most commonly prescribed pharmaceuticals, which allowed us to focus on the most environmentally relevant drugs potentially toxic to fish. Drugs with peak plasma concentration (Cmax) values were examined with a global database of surface water concentrations to predict potential risk for fish exposed to the most biologically active compounds. To prioritize the APIs most likely to cause adverse effects for fish, we limited the list to those with a response ratio ([plasma]/1%Cmax) ≥ 1 (n = 57) and those APIs without exposure concentrations exhibiting a 1%Cmax value ≤ 0.1 ng/ml (n = 50). The majority (n = 63) of the top prioritized APIs on this list fell into six drug classes: hormones (n = 21), antidepressants (n = 13), antihistamines (n = 8), anticholinergics (n = 4), corticosteroids (n = 4), and antihypertensives (n = 13). The FPM is advantageous because it is based on expected low-dose in vivo biological effects resulting from chemicals designed to interact with a specific target. Currently, the FPM is mostly limited to pharmaceuticals; however, this approach can be expanded to other chemicals with toxicity data expressed as a plasma concentration.