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- Title
A drug‐disease model for predicting survival in an Ebola outbreak.
- Authors
Toroghi, Masood Khaksar; Al‐Huniti, Nidal; Davis, John D.; DiCioccio, A. Thomas; Rippley, Ronda; Baum, Alina; Kyratsous, Christos A.; Sivapalasingam, Sumathi; Kantrowitz, Joel; Kamal, Mohamed A.
- Abstract
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.
- Subjects
ASPARTATE aminotransferase; EBOLA virus disease; EBOLA virus; BLOOD urea nitrogen; ORDINARY differential equations; RHESUS monkeys; HELLP syndrome
- Publication
CTS: Clinical & Translational Science, 2022, Vol 15, Issue 10, p2538
- ISSN
1752-8054
- Publication type
Article
- DOI
10.1111/cts.13383