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Prioritization of pharmaceuticals for potential environmental hazard through leveraging a large‐scale mammalian pharmacological dataset
Author(s) -
Berninger Jason P.,
LaLone Carlie A.,
Villeneuve Daniel L.,
Ankley Gerald T.
Publication year - 2016
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.2965
Subject(s) - prioritization , hazard , scale (ratio) , hazard analysis , environmental hazard , environmental science , environmental toxicology , environmental resource management , ecology , biology , geography , chemistry , toxicity , engineering , cartography , management science , organic chemistry , aerospace engineering
The potential for pharmaceuticals in the environment to cause adverse ecological effects is of increasing concern. Given the thousands of active pharmaceutical ingredients (APIs) that can enter the aquatic environment through human and/or animal (e.g., livestock) waste, a current challenge in aquatic toxicology is identifying those that pose the greatest risk. Because empirical toxicity information for aquatic species is generally lacking for pharmaceuticals, an important data source for prioritization is that generated during the mammalian drug development process. Applying concepts of species read‐across, mammalian pharmacokinetic data were used to systematically prioritize APIs by estimating their potential to cause adverse biological consequences to aquatic organisms, using fish as an example. Mammalian absorption, distribution, metabolism, and excretion (ADME) data (e.g., peak plasma concentration, apparent volume of distribution, clearance rate, and half‐life) were collected and curated, creating the Mammalian Pharmacokinetic Prioritization For Aquatic Species Targeting (MaPPFAST) database representing 1070 APIs. From these data, a probabilistic model and scoring system were developed and evaluated. Individual APIs and therapeutic classes were ranked based on clearly defined read‐across assumptions for translating mammalian‐derived ADME parameters to estimate potential hazard in fish (i.e., greatest predicted hazard associated with lowest mammalian peak plasma concentrations, total clearance and highest volume of distribution, half‐life). It is anticipated that the MaPPFAST database and the associated API prioritization approach will help guide research and/or inform ecological risk assessment. Environ Toxicol Chem 2016;35:1007–1020. Published 2015 Wiley Periodicals Inc. on behalf of SETAC. This article is a US Government work and, as such, is in the public domain in the United States of America.