title: Pharmaceuticals in the environment: good practice in predicting acute ecotoxicological effects.
abstract: Improvements in analytical techniques have led to an increased awareness of the presence of pharmaceuticals in the environment. Concern is now raised as to the potential adverse effects these compounds may have on non-target organisms, particularly under conditions of chronic exposure. There is a paucity of experimental ecotoxicity data available for pharmaceuticals, hence the use of in silico tools to predict toxicity is a pragmatic option. Previous studies have used the ECOSAR program to predict environmental toxicity of pharmaceuticals, however, these models were developed using industrial chemicals and the applicability of the models to predict effects of pharmaceuticals should be carefully considered. In this study ECOSAR was used to assign 364 diverse pharmaceuticals to recognised chemical classes and hence predict their aquatic toxicity. Confidence in the predictions was assessed in terms of whether the assigned class was realistically representative of the pharmaceutical in question. The correlation between experimentally determined toxicity values (where these were available) and those predicted by ECOSAR was investigated in terms of confidence in the prediction. ECOSAR was shown to make reasonable predictions for certain pharmaceuticals considered to be within the applicability domain of the models, but predictions were less reliable for compounds judged to fall outwith the domain of the models. This study is not critical of ECOSAR or the class based approach to predicting toxicity, but demonstrates the importance of using expert judgement to ascertain whether or not use of a particular model is appropriate when the specific chemistry of a query compound is considered.
authors.affiliation: School of Pharmacy and Chemistry, Liverpool John Moores University, Byrom Street, England L3 3AF, UK. j.madden@ljmu.ac.uk
authors.forename: Judith C
authors.initials: JC
authors.lastname: Madden
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Enoch
authors.forename: Mark
authors.initials: M
authors.lastname: Hewitt
authors.forename: Mark T D
authors.initials: MT
authors.lastname: Cronin
mesh_terms: D000818:Animals; D003621:Daphnia / Q000187:drug effects / Q000254:growth & development; D054750:Ecotoxicology; D056890:Eukaryota / Q000187:drug effects / Q000254:growth & development; D005399:Fishes / Q000254:growth & development; D020128:Inhibitory Concentration 50; D008962:Models, Theoretical; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000032:analysis* / Q000737:chemistry; D011237:Predictive Value of Tests; D014874:Water Pollutants, Chemical / Q000032:analysis* / Q000737:chemistry / Q000633:toxicity*
chemical_list: D004364:Pharmaceutical Preparations; D014874:Water Pollutants, Chemical