Kar Supratik, Roy Kunal, Leszczynski Jerzy
Interdisciplinary Center for Nanotoxicity, Department of Chemistry and Biochemistry, Jackson State University, Jackson, MS, USA.
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
Methods Mol Biol. 2018;1800:395-443. doi: 10.1007/978-1-4939-7899-1_19.
An extensive use of pharmaceuticals and the widespread practices of their erroneous disposal measures have made these products contaminants of emerging concern (CEC). Especially, active pharmaceutical ingredients (APIs) are ubiquitously detected in surface water and soil, mainly in the aquatic compartment, where they do affect the living systems. Unfortunately, there is a huge gap in the availability of ecotoxicological data on pharmaceuticals' environmental behavior and ecotoxicity which force EMEA (European Medicines Agency) to release guidelines for their risk assessment. In silico modeling approaches are vital tools to exploit the existing information to rapidly emphasize the potentially most hazardous and toxic pharmaceuticals and prioritize the most environmentally hazardous ones for focusing further on their experimental studies. The quantitative structure-activity relationship (QSAR) models are capable of predicting missing properties for toxic end-points required to prioritize existing, or newly synthesized chemicals for their potential hazard. This chapter reviews the information regarding occurrence and impact of pharmaceuticals and their metabolites in the environment along with their persistence, environmental fate, risk assessment, and risk management. A bird's eye view about the necessity of in silico methods for fate prediction of pharmaceuticals in the environment as well as existing successful models regarding ecotoxicity of pharmaceuticals are discussed. Available toxicity endpoints, ecotoxicity databases, and expert systems frequently used for ecotoxicity predictions of pharmaceuticals are also reported. The overall discussion justifies the requirement to build up additional in silico models for quick prediction of ecotoxicity of pharmaceuticals economically, without or involving only limited animal testing.
药品的广泛使用及其错误处置措施的普遍做法,使这些产品成为新出现的关注污染物(CEC)。特别是,活性药物成分(API)在地表水和土壤中普遍被检测到,主要存在于水生环境中,在那里它们确实会影响生物系统。不幸的是,关于药品环境行为和生态毒性的生态毒理学数据存在巨大差距,这迫使欧洲药品管理局(EMEA)发布其风险评估指南。计算机模拟方法是利用现有信息快速突出潜在最危险和有毒药品,并将对环境危害最大的药品进行优先排序以便进一步专注于其实验研究的重要工具。定量构效关系(QSAR)模型能够预测对现有或新合成化学品的潜在危害进行优先排序所需的毒性终点的缺失属性。本章回顾了有关药品及其代谢物在环境中的存在、影响以及它们的持久性、环境归宿、风险评估和风险管理的信息。讨论了关于计算机模拟方法对环境中药物归宿预测的必要性的鸟瞰图,以及现有的关于药物生态毒性的成功模型。还报告了常用于药物生态毒性预测的可用毒性终点、生态毒性数据库和专家系统。总体讨论证明了建立额外的计算机模拟模型以经济地快速预测药物生态毒性的必要性,无需或仅涉及有限的动物试验。