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跨物种生物数据外推以指导药物的环境安全性评估——现状与未来重点。

Cross-Species Extrapolation of Biological Data to Guide the Environmental Safety Assessment of Pharmaceuticals-The State of the Art and Future Priorities.

机构信息

Institute of Pharmaceutical Science, Faculty of Life Sciences & Medicine, King's College London, London, United Kingdom.

Global Sustainability, AstraZeneca, Macclesfield, Cheshire, United Kingdom.

出版信息

Environ Toxicol Chem. 2024 Mar;43(3):513-525. doi: 10.1002/etc.5634. Epub 2023 May 26.

DOI:10.1002/etc.5634
PMID:37067359
Abstract

The extrapolation of biological data across species is a key aspect of biomedical research and drug development. In this context, comparative biology considerations are applied with the goal of understanding human disease and guiding the development of effective and safe medicines. However, the widespread occurrence of pharmaceuticals in the environment and the need to assess the risk posed to wildlife have prompted a renewed interest in the extrapolation of pharmacological and toxicological data across the entire tree of life. To address this challenge, a biological "read-across" approach, based on the use of mammalian data to inform toxicity predictions in wildlife species, has been proposed as an effective way to streamline the environmental safety assessment of pharmaceuticals. Yet, how effective has this approach been, and are we any closer to being able to accurately predict environmental risk based on known human risk? We discuss the main theoretical and experimental advancements achieved in the last 10 years of research in this field. We propose that a better understanding of the functional conservation of drug targets across species and of the quantitative relationship between target modulation and adverse effects should be considered as future research priorities. This pharmacodynamic focus should be complemented with the application of higher-throughput experimental and computational approaches to accelerate the prediction of internal exposure dynamics. The translation of comparative (eco)toxicology research into real-world applications, however, relies on the (limited) availability of experts with the skill set needed to navigate the complexity of the problem; hence, we also call for synergistic multistakeholder efforts to support and strengthen comparative toxicology research and education at a global level. Environ Toxicol Chem 2024;43:513-525. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

摘要

跨物种的生物数据推断是生物医药研究和药物开发的关键方面。在这种情况下,应用比较生物学的考虑因素是为了理解人类疾病并指导有效和安全药物的开发。然而,由于药物在环境中的广泛存在,以及需要评估其对野生动物构成的风险,人们重新关注将药理学和毒理学数据推断到整个生命之树上。为了解决这一挑战,提出了一种基于使用哺乳动物数据来为野生动物物种的毒性预测提供信息的生物学“read-across”方法,作为简化药物环境安全性评估的有效方法。但是,这种方法的效果如何,我们是否更接近于能够根据已知的人类风险准确预测环境风险?我们讨论了该领域过去 10 年研究中取得的主要理论和实验进展。我们建议,更好地理解药物靶点在物种间的功能保守性,以及目标调节与不良反应之间的定量关系,应被视为未来的研究重点。这种药效学重点应辅以应用高通量实验和计算方法,以加速内部暴露动力学的预测。然而,将比较(生态)毒理学研究转化为实际应用,取决于具有必要技能的专家的(有限)可用性,以应对问题的复杂性;因此,我们还呼吁多利益相关者协同努力,以支持和加强全球范围内的比较毒理学研究和教育。环境毒物化学 2024;43:513-525。© 2023 作者。环境毒物化学由 Wiley Periodicals LLC 代表 SETAC 出版。

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