Regeneron Pharmaceuticals, Inc., Tarrytown, New York, USA.
Formerly of Regeneron Pharmaceuticals, Inc., Tarrytown, New York, USA.
Clin Transl Sci. 2022 Oct;15(10):2538-2550. doi: 10.1111/cts.13383. Epub 2022 Aug 17.
REGN-EB3 (Inmazeb) is a cocktail of three human monoclonal antibodies approved for treatment of Ebola infection. This paper describes development of a mathematical model linking REGN-EB3's inhibition of Ebola virus to survival in a non-human primate (NHP) model, and translational scaling to predict survival in humans. Pharmacokinetic/pharmacodynamic data from single- and multiple-dose REGN-EB3 studies in infected rhesus macaques were incorporated. Using discrete indirect response models, the antiviral mechanism of action was used as a forcing function to drive the reversal of key Ebola disease hallmarks over time, for example, liver and kidney damage (elevated alanine [ALT] and aspartate aminotransferases [AST], blood urea nitrogen [BUN], and creatinine), and hemorrhage (decreased platelet count). A composite disease characteristic function was introduced to describe disease severity and integrated with the ordinary differential equations estimating the time course of clinical biomarkers. Model simulation results appropriately represented the concentration-dependence of the magnitude and time course of Ebola infection (viral and pathophysiological), including time course of viral load, ALT and AST elevations, platelet count, creatinine, and BUN. The model estimated the observed survival rate in rhesus macaques and the dose of REGN-EB3 required for saturation of the pharmacodynamic effects of viral inhibition, reversal of Ebola pathophysiology, and survival. The model also predicted survival in clinical trials with appropriate scaling to humans. This mathematical investigation demonstrates that drug-disease modeling can be an important translational tool to integrate preclinical data from an NHP model recapitulating disease progression to guide future translation of preclinical data to clinical study design.
REGN-EB3（Inmazeb）是一种三种人源单克隆抗体的鸡尾酒疗法，已被批准用于治疗埃博拉病毒感染。本文描述了一种将 REGN-EB3 抑制埃博拉病毒与非人类灵长类动物（NHP）模型中的存活相关联的数学模型的开发，以及对人类进行转化性预测的方法。从感染恒河猴的 REGN-EB3 单次和多次剂量研究中纳入了药代动力学/药效学数据。使用离散间接反应模型，将抗病毒作用机制作为强制函数，随着时间的推移逆转埃博拉疾病的关键标志，例如肝和肾损伤（丙氨酸[ALT]和天冬氨酸转氨酶[AST]升高、血尿素氮[BUN]和肌酐）和出血（血小板计数减少）。引入了一种复合疾病特征函数来描述疾病严重程度，并与估计临床生物标志物时间过程的常微分方程集成。模型模拟结果适当地描述了埃博拉感染（病毒和病理生理学）的幅度和时间过程的浓度依赖性，包括病毒载量、ALT 和 AST 升高、血小板计数、肌酐和 BUN 的时间过程。该模型估计了恒河猴中的观察到的存活率以及需要达到 REGN-EB3 药效动力学效应、逆转埃博拉病理生理学和存活所需的剂量。该模型还预测了临床试验中的存活率，并适当转化为人类。这项数学研究表明，药物-疾病建模可以成为一种重要的转化工具，将来自模拟疾病进展的 NHP 模型的临床前数据整合在一起，以指导将临床前数据转化为临床研究设计。
