Dixit Vaibhav A, Singh Pragati
Department of Pharmacy, Birla Institute of Technology and Sciences Pilani (BITS Pilani), Vidya Vihar Campus, Street number 41, Pilani, Rajasthan 333031 India.
In Silico Pharmacol. 2021 May 15;9(1):37. doi: 10.1007/s40203-021-00096-9. eCollection 2021.
Toxicity related failures in drug discovery and clinical development have motivated scientists and regulators to develop a wide range of in-vitro, in-silico tools coupled with data science methods. Older drug discovery rules are being constantly modified to churn out any hidden predictive value. Nonetheless, the dose-response concepts remain central to all these methods. Over the last 2 decades medicinal chemists, and pharmacologists have observed that different physicochemical, and pharmacological properties capture trends in toxic responses. We propose that these observations should be viewed in a comprehensive property-response framework where dose is only a factor that modifies the inherent toxicity potential. We then introduce the recently proposed "Drug Toxicity Index (DTI)" and briefly summarize its applications. A webserver is available to calculate DTI values (https://all-tool-kit.github.io/Web-Tool.html).
药物研发和临床开发中与毒性相关的失败促使科学家和监管机构开发了一系列体外、计算机模拟工具以及数据科学方法。旧的药物研发规则不断被修改,以挖掘任何潜在的预测价值。尽管如此,剂量反应概念仍然是所有这些方法的核心。在过去20年里,药物化学家与药理学家观察到,不同的物理化学和药理特性反映出毒性反应的趋势。我们建议,应在一个综合的特性-反应框架中看待这些观察结果,其中剂量只是改变内在毒性潜力的一个因素。然后,我们介绍最近提出的“药物毒性指数(DTI)”并简要总结其应用。可通过一个网络服务器来计算DTI值(https://all-tool-kit.github.io/Web-Tool.html)。