用于对乙酰氨基酚肝毒性预测的虚拟可扩展肝叶模型

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES NPJ Digital Medicine Pub Date : 2024-11-28 DOI:10.1038/s41746-024-01349-5
Stelian Camara Dit Pinto, Jalal Cherkaoui, Debarshi Ghosh, Valentine Cazaubon, Kenza E. Benzeroual, Steven M. Levine, Mohammed Cherkaoui, Gagan K. Sood, Sharmila Anandasabapathy, Sadhna Dhingra, John M. Vierling, Nicolas R. Gallo
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引用次数: 0

摘要

解决药物引起的肝损伤问题在药物开发过程中至关重要,这往往会导致 III 期试验失败和退出市场。传统的动物模型无法准确预测人体肝脏的毒性。人体器官虚拟双胞胎是一种很有前景的解决方案。我们介绍了虚拟肝叶,它是多尺度肝脏虚拟孪生模型 "活肝 "的基础元素。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,可预测患者特有的肝细胞损伤模式。通过结合代谢分区,我们的预测结果与临床分区肝毒性观察结果一致。这种方法推动了人类肝脏虚拟孪生的发展,有助于预测和验证药物诱导的肝损伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A virtual scalable model of the Hepatic Lobule for acetaminophen hepatotoxicity prediction
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.
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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