In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

中文翻译：

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用于合理药物设计的计算机 ADME/T 建模

近几十年来，计算机吸收、分布、代谢、排泄 (ADME) 和毒性 (T) 建模作为合理药物设计的工具受到了药学科学家的广泛关注，并且已经报道了各种与 ADME/T 相关的预测模型。这些模型的高通量和低成本特性允许更简化的药物开发过程，其中可以基于对生物利用度和安全性以及活性的平行研究来指导命中的识别或其结构优化。然而，这些工具的有效性在很大程度上取决于它们应对不同阶段需求的能力，例如，由于缺乏所需的可预测性，它们在候选人选择中的使用受到了限制。对于一些涉及更复杂机制的事件或端点，当前计算机方法仍需进一步改进。在这篇评论中，我们将简要介绍计算机一些物理化学参数、ADME 特性和毒性评价的模型，重点介绍其建模方法、它们在药物发现中的应用以及这些模型的潜在优点或不足。最后，将讨论基于大数据分析和系统科学的未来 ADME/T 建模的前景。