Schultz Terry W, Cronin Mark T D
The University of Tennessee, College of Veterinary Medicine, 2407 River Drive, Knoxville, TN, 37996-4543, USA.
School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, L3 3AF, Liverpool, England, UK.
Regul Toxicol Pharmacol. 2017 Aug;88:185-191. doi: 10.1016/j.yrtph.2017.06.011. Epub 2017 Jun 24.
A series of case studies designed to further acceptance of read-across predictions, especially for chronic health-related endpoints, have been evaluated with regard to the knowledge and insight they provide. A common aim of these case studies was to examine sources of uncertainty associated with read-across. While uncertainty is related to the quality and quantity of the read across endpoint data, uncertainty also includes a variety of other factors, the foremost of which is uncertainty associated with the justification of similarity and quantity and quality of data for the source chemical(s). This investigation has demonstrated that the assessment of uncertainty associated with a similarity justification includes consideration of the information supporting the scientific arguments and the data associated with the chemical, toxicokinetic and toxicodynamic similarity. Similarity in chemistry is often not enough to justify fully a read-across prediction, thus, for chronic health endpoints, toxicokinetic and/or toxicodynamic similarity is essential. Data from New Approach Methodology(ies) including high throughput screening, in vitro and in chemico assay and in silico tools, may provide critical information needed to strengthen the toxicodynamic similarity rationale. In addition, it was shown that toxicokinetic (i.e., ADME) similarity, especially metabolism, is often the driver of the overall uncertainty.
为进一步促进类推预测（尤其是针对与慢性健康相关的终点）的接受度而设计的一系列案例研究，已根据其所提供的知识和见解进行了评估。这些案例研究的一个共同目标是检查与类推相关的不确定性来源。虽然不确定性与类推终点数据的质量和数量有关，但不确定性还包括各种其他因素，其中最主要的是与源化学物质的相似性论证以及数据的数量和质量相关的不确定性。这项调查表明，与相似性论证相关的不确定性评估包括对支持科学论据的信息以及与化学、毒代动力学和毒效动力学相似性相关的数据的考虑。化学相似性通常不足以充分证明类推预测的合理性，因此，对于慢性健康终点而言，毒代动力学和/或毒效动力学相似性至关重要。来自新方法学的数据，包括高通量筛选、体外和化学分析以及计算机工具，可能会提供加强毒效动力学相似性原理所需的关键信息。此外，研究表明毒代动力学（即吸收、分布、代谢和排泄）相似性，尤其是代谢，往往是总体不确定性的驱动因素。
