Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee 37830, USA.
Toxicol Sci. 2021 Sep 28;183(2):285-301. doi: 10.1093/toxsci/kfab091.
Using in vitro data to estimate point of departure (POD) values is an essential component of new approach methodologies (NAMs)-based chemical risk assessments. In this case study, we evaluated a NAM for hepatotoxicity based on rat primary hepatocytes, high-content imaging (HCI), and toxicokinetic modeling. First, we treated rat primary hepatocytes with 10 concentrations (0.2-100 µM) of 51 chemicals that produced hepatotoxicity in repeat-dose subchronic and chronic exposures. Second, we used HCI to measure endoplasmic reticulum stress, mitochondrial function, lysosomal mass, steatosis, apoptosis, DNA texture, nuclear size, and cell number at 24, 48, and 72 h and calculated concentrations at 50% maximal activity (AC50). Third, we estimated administered equivalent doses (AEDs) from AC50 values using toxicokinetic modeling. AEDs using physiologically based toxicokinetic models were 4.1-fold (SD 6.3) and 8.1-fold (SD 15.5) lower than subchronic and chronic lowest observed adverse effect levels (LOAELs), respectively. In contrast, AEDs from ToxCast and Tox21 assays were 89.8-fold (SD 149.5) and 168-fold (SD 323.7) lower than subchronic and chronic LOAELs. Individual HCI endpoints also estimated AEDs for specific hepatic lesions that were lower than in vivo PODs. Lastly, AEDs were similar for different in vitro exposure durations, but steady-state toxicokinetic models produced 7.6-fold lower estimates than dynamic physiologically based ones. Our findings suggest that NAMs from diverse cell types provide conservative estimates of PODs. In contrast, NAMs based on the same species and cell type as the adverse outcome may produce estimates closer to the traditional in vivo PODs.
利用体外数据估算基准剂量(POD)值是基于新方法学(NAM)的化学风险评估的一个重要组成部分。在本案例研究中,我们评估了一种基于大鼠原代肝细胞、高内涵成像(HCI)和毒代动力学建模的肝毒性 NAM。首先,我们用 51 种化学物质处理大鼠原代肝细胞,这些化学物质在重复剂量亚慢性和慢性暴露中产生肝毒性,浓度范围为 0.2-100 μM。其次,我们使用 HCI 测量内质网应激、线粒体功能、溶酶体质量、脂肪变性、凋亡、DNA 纹理、核大小和细胞数量,时间点为 24、48 和 72 小时,并计算半数最大活性(AC50)时的浓度。第三,我们使用毒代动力学模型从 AC50 值估算给药等效剂量(AED)。基于生理毒代动力学模型的 AED 分别比亚慢性和慢性最低观察到的不良效应水平(LOAEL)低 4.1 倍(SD 6.3)和 8.1 倍(SD 15.5)。相比之下,来自 ToxCast 和 Tox21 测定的 AED 分别比亚慢性和慢性 LOAEL 低 89.8 倍(SD 149.5)和 168 倍(SD 323.7)。单个 HCI 终点还估计了特定肝损伤的 AED,低于体内 POD。最后,不同的体外暴露时间的 AED 相似,但稳态毒代动力学模型产生的估计值比动态生理毒代动力学模型低 7.6 倍。我们的研究结果表明,来自不同细胞类型的 NAM 提供了 POD 的保守估计值。相比之下,基于与不良结局相同物种和细胞类型的 NAM 可能会产生更接近传统体内 POD 的估计值。