Prioritization of pharmaceuticals for potential environmental hazard through leveraging a large‐scale mammalian pharmacological dataset

摘要: The potential for pharmaceuticals in the environment to cause adverse ecological effects is of increasing concern. Given thousands active pharmaceutical ingredients (APIs) that can enter aquatic through human and/or animal (e.g., livestock) waste, a current challenge toxicology identifying those pose greatest risk. Because empirical toxicity information species generally lacking pharmaceuticals, an important data source prioritization generated during mammalian drug development process. Applying concepts read-across, pharmacokinetic were used systematically prioritize APIs by estimating their biological consequences organisms, using fish as example. Mammalian absorption, distribution, metabolism, and excretion (ADME) peak plasma concentration, apparent volume clearance rate, half-life) collected curated, creating Pharmacokinetic Prioritization For Aquatic Species Targeting (MaPPFAST) database representing 1070 APIs. From these data, probabilistic model scoring system developed evaluated. Individual therapeutic classes ranked based on clearly defined read-across assumptions translating mammalian-derived ADME parameters estimate hazard (i.e., predicted associated with lowest concentrations, total highest half-life). It anticipated MaPPFAST API approach will help guide research inform risk assessment.