Developmental and Reproductive Toxicology Research Group, Korea Institute of Toxicology, Daejeon, 34114, Republic of Korea.
Institute for Advanced Studies, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
Arch Toxicol. 2024 Nov;98(11):3897-3908. doi: 10.1007/s00204-024-03845-9. Epub 2024 Sep 5.
Individuals are exposed to a wide arrays of hazardous chemicals on a daily basis through various routes, many of which have not undergone comprehensive toxicity assessments. While traditional developmental toxicity tests involving pregnant animals are known for their reliability, they are also associated with high costs and time requirements. Consequently, there is an urgent demand for alternative, cost-efficient, and rapid in vitro testing methods. This study aims to address the challenges related to automating and streamlining the screening of early developmental toxicity of chemicals by introducing a mouse embryoid body test (EBT) model in a 384-ultra low attachment well format. Embryoid bodies (EBs) generated in this format were characterized by a spontaneous differentiation trajectory into cardiac mesoderm by as analyzed by RNA-seq. Assessing prediction accuracy using reference compounds suggested in the ICH S5(R3) guideline and prior studies resulted in the establishment of the acceptance criteria and applicability domain of the EBT model. The results indicated an 84.38% accuracy in predicting the developmental toxicity of 23 positive and 9 negative reference compounds, with an optimized cutoff threshold of 750 µM. Overall, the developed EBT model presents a promising approach for more rapid, high-throughput chemical screening, thereby facilitating well-informed decision-making in environmental management and safety assessments.
人们每天通过各种途径接触到广泛的有害化学物质，其中许多化学物质尚未经过全面的毒性评估。虽然涉及怀孕动物的传统发育毒性测试以其可靠性而闻名，但它们也存在成本高和时间要求长的问题。因此，迫切需要替代的、具有成本效益的、快速的体外测试方法。本研究旨在通过引入一种 384 孔超低附着孔板格式的小鼠类胚体测试（EBT）模型，解决化学物质早期发育毒性筛选自动化和简化的相关挑战。通过 RNA-seq 分析，这种格式生成的类胚体（EBs）表现出自发分化为心脏中胚层的轨迹。使用 ICH S5(R3)指南和先前研究中建议的参考化合物评估预测准确性，从而确定了 EBT 模型的接受标准和适用域。结果表明，在预测 23 种阳性和 9 种阴性参考化合物的发育毒性方面，该模型的准确率为 84.38%，优化的截断阈值为 750µM。总的来说，开发的 EBT 模型为更快速、高通量的化学筛选提供了一种有前途的方法，从而有助于在环境管理和安全评估中做出明智的决策。
