Adolphe Merkle Institute, University of Fribourg, Chemin des Verdiers 4, 1700 Fribourg, Switzerland.
Lung Precision Medicine (LPM), Department for BioMedical Research (DBMR), University of Bern, Bern, Switzerland.
Chem Res Toxicol. 2024 Oct 21;37(10):1601-1611. doi: 10.1021/acs.chemrestox.4c00113. Epub 2024 Aug 8.
With numerous novel and innovative models emerging every year to reduce or replace animal testing, there is an urgent need to align the design, harmonization, and validation of such systems using extrapolation (IVIVE) approaches. In particular, in inhalation toxicology, there is a lack of predictive and prevalidated lung models that can be considered a valid alternative for animal testing. The predictive power of such models can be enhanced by applying the Adverse Outcome Pathways (AOP) framework, which casually links key events (KE) relevant to IVIVE. However, one of the difficulties identified is that the endpoint analysis and readouts of specific assays in and animal models for specific toxicants are currently not harmonized, making the alignment challenging. We summarize the current state of the art in endpoint analysis in the two systems, focusing on inflammatory-induced effects and providing guidance for future research directions to improve the alignment.
每年都有大量新颖创新的模型涌现，旨在减少或替代动物测试，因此迫切需要使用外推（IVIVE）方法来调整这些系统的设计、协调和验证。特别是在吸入毒理学中，缺乏可预测和经过预验证的肺模型，这些模型可以被视为动物测试的有效替代方法。通过应用不良结局途径（AOP）框架，可以增强这些模型的预测能力，该框架偶然地将与 IVIVE 相关的关键事件（KE）联系起来。然而，确定的困难之一是，目前针对特定毒物，在人和动物模型中，特定检测的终点分析和读出尚未协调，这使得调整具有挑战性。我们总结了这两个系统中终点分析的最新技术状态，重点关注炎症诱导的影响，并为未来的研究方向提供指导，以改善调整。
