PRIORITIZATION OF PHARMACEUTICALS FOR POTENTIAL ENVIRONMENTAL HAZARD THROUGH LEVERAGING A LARGE-SCALE MAMMALIAN PHARMACOLOGICAL DATASET
PRIORITIZATION OF PHARMACEUTICALS FOR POTENTIAL ENVIRONMENTAL HAZARD THROUGH LEVERAGING A LARGE-SCALE MAMMALIAN PHARMACOLOGICAL DATASET
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DOI：
10.1002/etc.2965
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发表时间：
2016-04-01
影响因子：
4.1
通讯作者：
Ankley, Gerald T.
中科院分区：
文献类型：
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作者：
Berninger, Jason P.;LaLone, Carlie A.;Ankley, Gerald T.
环境中的药物可能造成不利的生态影响，这一点日益受到关注。鉴于数千种活性药物成分（API）可以通过人类和/或动物（例如，牲畜）废物，水生毒理学目前的挑战是确定那些构成最大风险的。由于水生物种的经验毒性信息通常缺乏药物，优先级的一个重要数据来源是在哺乳动物药物开发过程中产生的。应用物种交叉概念，使用哺乳动物药代动力学数据，通过估计其对水生生物造成不良生物后果的可能性（以鱼类为例），系统地确定原料药的优先顺序。哺乳动物吸收、分布、代谢和排泄（ADME）数据（例如，血浆峰浓度、表观分布容积、清除率和半衰期），创建了代表1070种API的水生物种靶向哺乳动物药代动力学优先级（MaPPFAST）数据库。根据这些数据，开发并评估了概率模型和评分系统。基于明确定义的交叉阅读假设，对单个API和治疗类别进行排名，以转换由西氏衍生的ADME参数，以估计鱼类中的潜在危害（即，与最低哺乳动物血浆峰浓度、总清除率和最高分布容积、半衰期相关的最大预测危害）。预计MapPFAST数据库和相关的API优先排序方法将有助于指导研究和/或为生态风险评估提供信息。出版社：Wiley Periodicals Inc.关于SETAC本条目属于美国政府作品，因此在美国属于公有领域。
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. 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.