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Modelling Ebola virus dynamics: Implications for therapy.

Modelling Ebola virus dynamics: Implications for therapy.
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Martyushev A, Nakaoka S, Sato K, Noda T, Iwami S,


Martyushev A, Nakaoka S, Sato K, Noda T, Iwami S, (click to view)

Martyushev A, Nakaoka S, Sato K, Noda T, Iwami S,

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Antiviral research 2016 Oct 12() pii 10.1016/j.antiviral.2016.10.004

Abstract

Ebola virus (EBOV) causes a severe, often fatal Ebola virus disease (EVD), for which no approved antivirals exist. Recently, some promising anti-EBOV drugs, which are experimentally potent in animal models, have been developed. However, because the quantitative dynamics of EBOV replication in humans is uncertain, it remains unclear how much antiviral suppression of viral replication affects EVD outcome in patients. Here, we developed a novel mathematical model to quantitatively analyse human viral load data obtained during the 2000/01 Uganda EBOV outbreak and evaluated the effects of different antivirals. We found that nucleoside analogue- and siRNA-based therapies are effective if a therapy with a >50% inhibition rate is initiated within a few days post-symptom-onset. In contrast, antibody-based therapy requires not only a higher inhibition rate but also an earlier administration, especially for otherwise fatal cases. Our results demonstrate that an appropriate choice of EBOV-specific drugs is required for effective EVD treatment.

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