Tuesuwan Bodin, Vongsutilers Vorasit
Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand.
Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand.
J Pharm Sci. 2023 May;112(5):1192-1209. doi: 10.1016/j.xphs.2023.01.028. Epub 2023 Feb 4.
The current global situation of nitrosamine contamination has expanded from angiotensin-II receptor blockers (ARBs) to wide range of medicines as the risk of contamination via the drug substances, formulation, manufacturing process, and packaging is possible for many drug products. The understanding of chemistry, toxicology, and root causes of nitrosamines are mandatory to effectively evaluate and mitigate the risks associated with the contaminated mutagen. Lessons learnt and scientific findings from previously identified root causes are good examples on how to perform effective risk assessments and establish control strategies. Addressing the risk of nitrosamine contamination in pharmaceuticals requires significant knowledge and considerable resources to collect the necessary information for risk evaluation. Examples of the resources required include a reliable laboratory facility, reference material, highly specific and sensitive instrumentation able handle trace levels of contamination, data management, and the most limited resource - time. Therefore, the supporting tools to assist with risk assessment e.g., shared databases for drug and excipients in concern, screening models for the determination of nitrosamine formation potential, and an in silico model to help with toxicity estimation, have proven to be beneficial to tackle the risk and concern of nitrosamine contamination in pharmaceuticals.
当前全球亚硝胺污染情况已从血管紧张素 II 受体阻滞剂(ARBs)扩展到多种药物,因为许多药品都有可能通过原料药、制剂、生产工艺和包装受到污染。了解亚硝胺的化学性质、毒理学及根本原因,对于有效评估和降低与受污染诱变剂相关的风险至关重要。从先前确定的根本原因中吸取的经验教训和科学发现,是如何进行有效风险评估和制定控制策略的良好范例。解决药品中亚硝胺污染风险需要大量知识和相当多资源来收集风险评估所需的必要信息。所需资源的例子包括可靠的实验室设施、参考材料、能够处理痕量污染水平的高特异性和高灵敏度仪器、数据管理,以及最稀缺的资源——时间。因此,有助于风险评估的支持工具,例如有关药物和辅料的共享数据库、用于确定亚硝胺形成潜力的筛选模型,以及有助于毒性估计的计算机模拟模型,已被证明有利于应对药品中亚硝胺污染的风险和问题。