Across the spectrum of industrial sectors, including pharmaceuticals, chemicals, personal care products, food additives and their associated regulatory agencies, there is a need to develop robust and reliable methods to reduce or replace animal testing. It is generally recognised that no single alternative method will be able to provide a one-to-one replacement for assays based on more complex toxicological endpoints. Hence, information from a combination of techniques is required. A greater understanding of the time and concentration-dependent mechanisms, underlying the interactions between chemicals and biological systems, and the sequence of events that can lead to apical effects, will help to move forward the science of reducing and replacing animal experiments. In silico modelling, in vitro assays, high-throughput screening, organ-on-a-chip technology, omics and mathematical biology, can provide complementary information to develop a complete picture of the potential response of an organism to a chemical stressor. Adverse outcome pathways (AOPs) and systems biology frameworks enable relevant information from diverse sources to be logically integrated. While individual researchers do not need to be experts across all disciplines, it is useful to have a fundamental understanding of what other areas of science have to offer, and how knowledge can be integrated with other disciplines. The purpose of this review is to provide those who are unfamiliar with predictive in silico tools, with a fundamental understanding of the underlying theory. Current applications, software, barriers to acceptance, new developments and the use of integrated approaches are all discussed, with additional resources being signposted for each of the topics.

中文翻译：

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作为动物试验替代品的 In Silico 工具综述：原理、资源和应用

在包括制药、化学品、个人护理产品、食品添加剂及其相关监管机构在内的各个工业部门，都需要开发稳健可靠的方法来减少或取代动物试验。人们普遍认为，没有单一的替代方法能够为基于更复杂毒理学终点的检测提供一对一的替代方法。因此，需要来自技术组合的信息。对化学和生物系统之间相互作用的时间和浓度依赖性机制以及可能导致顶端效应的事件顺序有更深入的了解，将有助于推动减少和替代动物实验的科学。计算机模拟、体外分析、高通量筛选、器官芯片技术、组学和数学生物学可以提供补充信息，以全面了解生物体对化学压力源的潜在反应。不良结局途径 (AOP) 和系统生物学框架使来自不同来源的相关信息能够在逻辑上整合。虽然个别研究人员不需要是所有学科的专家，但对其他科学领域必须提供的内容以及知识如何与其他学科相结合有一个基本的了解是很有用的。本综述的目的是为那些不熟悉计算机预测工具的人提供对基本理论的基本理解。讨论了当前的应用程序、软件、接受障碍、新发展和集成方法的使用，