Zhang, Shengyuan;
Agyeman, Akosua A;
Hadjichrysanthou, Christoforos;
Standing, Joseph F;
(2023)
SARS-CoV-2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy.
CPT: Pharmacometrics and Systems Pharmacology
10.1002/psp4.13022.
(In press).
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Abstract
Mathematical models of viral dynamics have been reported to describe adequately the dynamical changes of SARS-CoV-2 viral load within an individual host. In this study, eight published viral dynamic models were assessed, and model selection was performed. Viral load data were collected from a community surveillance study, including 2155 measurements from 162 patients (124 household and 38 non-household contacts). An extended version of the target-cell limited model that includes an eclipse phase and an immune response component that enhances viral clearance described best the data. In general, the parameter estimates showed good precision (relative standard error <10), apart from the death rate of infected cells. The parameter estimates were used to simulate the outcomes of a clinical trial of the antiviral AZD7442, a monoclonal antibody combination which blocks infection of the target cells by neutralising the virus. The simulated outcome of the effectiveness of the antiviral therapy in controlling viral replication was in a good agreement with the clinical trial data. Early treatment with high antiviral efficacy is important for desired therapeutic outcome.
Type: | Article |
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Title: | SARS-CoV-2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/psp4.13022 |
Publisher version: | https://doi.org/10.1002/psp4.13022 |
Language: | English |
Additional information: | © 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Infection, Immunity and Inflammation Dept |
URI: | https://discovery.ucl.ac.uk/id/eprint/10175749 |
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