Addressing drug-induced liver injury is crucial in drug development, often causing Phase III trial failures and market withdrawals. Traditional animal models fail to predict human liver toxicity accurately. Virtual twins of human organs present a promising solution. We introduce the Virtual Hepatic Lobule, a foundational element of the Living Liver, a multi-scale liver virtual twin. This model integrates blood flow dynamics and an acetaminophen-induced injury model to predict hepatocyte injury patterns specific to patients. By incorporating metabolic zonation, our predictions align with clinical zonal hepatotoxicity observations. This methodology advances the development of a human liver virtual twin, aiding in the prediction and validation of drug-induced liver injuries.

解决药物性肝损伤在药物开发中至关重要，这通常会导致 III 期试验失败和市场退出。传统的动物模型无法准确预测人类肝脏毒性。人体器官的虚拟孪生提出了一个很有前途的解决方案。我们介绍了虚拟肝小叶，这是多尺度肝脏虚拟孪生 Living Liver 的基本元素。该模型整合了血流动力学和对乙酰氨基酚诱导的损伤模型，以预测患者特有的肝细胞损伤模式。通过结合代谢分区，我们的预测与临床分区肝毒性观察一致。这种方法推进了人类肝脏虚拟孪生的开发，有助于预测和验证药物诱导的肝损伤。