Zwickl Craig M, Graham Jessica, Jolly Robert, Bassan Arianna, Ahlberg Ernst, Amberg Alexander, Anger Lennart T, Barton-Maclaren Tara, Beilke Lisa, Bellion Phillip, Brigo Alessandro, Cronin Mark T D, Custer Laura, Devlin Amy, Burleigh-Flayers Heather, Fish Trevor, Glover Kyle, Glowienke Susanne, Gromek Kamila, Jones David, Karmaus Agnes, Kemper Ray, Piparo Elena Lo, Madia Federica, Martin Matthew, Masuda-Herrera Melisa, McAtee Britt, Mestre Jordi, Milchak Lawrence, Moudgal Chandrika, Mumtaz Moiz, Muster Wolfgang, Neilson Louise, Patlewicz Grace, Paulino Alexandre, Roncaglioni Alessandra, Ruiz Patricia, Suarez Diana, Szabo David T, Valentin Jean-Pierre, Vardakou Ioanna, Woolley David, Myatt Glenn
Transendix LLC, Indianapolis, IN 46229, USA.
Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
Comput Toxicol. 2022 Nov;24. doi: 10.1016/j.comtox.2022.100237. Epub 2022 Jul 14.
Acute models are being used to support an increasing number of application areas including (1) product research and development, (2) product approval and registration as well as (3) the transport, storage and handling of chemicals. The adoption of such models is being hindered, in part, because of a lack of guidance describing how to perform and document an analysis. To address this issue, a framework for an acute toxicity hazard assessment is proposed. This framework combines results from different sources including methods and or experiments. methods that can assist the prediction of outcomes (i.e., LD) are analyzed concluding that predictions obtained using approaches are now well-suited for reliably supporting assessment of LD-based acute toxicity for the purpose of GHS classification. A general overview is provided of the endpoints from studies commonly evaluated for predicting acute toxicity (e.g., cytotoxicity/cytolethality as well as assays targeting specific mechanisms). The increased understanding of pathways and key triggering mechanisms underlying toxicity and the increased availability of data allow for a shift away from assessments solely based on endpoints such as LD, to mechanism-based endpoints that can be accurately assessed or by using prediction models. This paper also highlights the importance of an expert review of all available information using weight-of-evidence considerations and illustrates, using a series of diverse practical use cases, how approaches support the assessment of acute toxicity.
急性模型正被用于支持越来越多的应用领域,包括:(1)产品研发;(2)产品批准与注册;以及(3)化学品的运输、储存和处理。此类模型的采用受到一定阻碍,部分原因是缺乏关于如何进行分析及记录分析过程的指导。为解决这一问题,本文提出了一个急性毒性危害评估框架。该框架整合了来自不同来源的结果,包括方法和/或实验。对有助于预测结果(即半数致死剂量)的方法进行了分析,得出结论:使用这些方法获得的预测结果现在非常适合可靠地支持基于半数致死剂量的急性毒性评估,以用于全球化学品统一分类和标签制度(GHS)的分类目的。本文对通常用于预测急性毒性的研究终点(例如细胞毒性/细胞致死性以及针对特定机制的检测方法)进行了总体概述。对毒性潜在途径和关键触发机制的深入理解以及更多数据的可得性,使得评估从单纯基于半数致死剂量等终点,转向可通过或使用预测模型进行准确评估的基于机制的终点。本文还强调了利用证据权重考量对所有可用信息进行专家评审的重要性,并通过一系列不同的实际应用案例说明了这些方法如何支持急性毒性评估。