Gilead Sciences, Inc., Nonclinical Safety and Pathobiology (NSP), Foster City, CA, USA.
Gilead Sciences, Inc., Nonclinical Safety and Pathobiology (NSP), Foster City, CA, USA.
Regul Toxicol Pharmacol. 2023 Aug;142:105415. doi: 10.1016/j.yrtph.2023.105415. Epub 2023 May 29.
Low levels of N-nitrosamines (NAs) were detected in pharmaceuticals and, as a result, health authorities (HAs) have published acceptable intakes (AIs) in pharmaceuticals to limit potential carcinogenic risk. The rationales behind the AIs have not been provided to understand the process for selecting a TD or read-across analog. In this manuscript we evaluated the toxicity data for eleven common NAs in a comprehensive and transparent process consistent with ICH M7. This evaluation included substances which had datasets that were robust, limited but sufficient, and substances with insufficient experimental animal carcinogenicity data. In the case of robust or limited but sufficient carcinogenicity information, AIs were calculated based on published or derived TDs from the most sensitive organ site. In the case of insufficient carcinogenicity information, available carcinogenicity data and structure activity relationships (SARs) were applied to categorical-based AIs of 1500 ng/day, 150 ng/day or 18 ng/day; however additional data (such as biological or additional computational modelling) could inform an alternative AI. This approach advances the methodology used to derive AIs for NAs.
低水平的 N-亚硝胺(NAs)在药品中被检测到,因此健康当局(HAs)已发布了药品中的可接受摄入量(AIs),以限制潜在的致癌风险。选择 TD 或读通类比物的理由并没有提供给人们了解这个过程。在本文中,我们以与 ICH M7 一致的全面透明的方式评估了十一种常见 NAs 的毒性数据。这项评估包括数据集强大、有限但足够以及实验动物致癌性数据不足的物质。对于强大或有限但足够的致癌性信息,根据最敏感的器官部位的已发表或推导的 TD 计算 AIs。在致癌性信息不足的情况下,应用现有的致癌性数据和结构活性关系(SARs),对 1500ng/天、150ng/天或 18ng/天的基于分类的 AIs 进行分类;但是,额外的数据(如生物或额外的计算建模)可以为替代 AI 提供信息。这种方法推进了为 NAs 推导 AIs 所使用的方法。