SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy
Abstract Mathematical models of viral dynamics have been reported to describe adequately the dynamic changes of severe acute respiratory syndrome‐coronavirus 2 viral load within an individual host. In this study, eight published viral dynamic models were assessed, and model selection was performed....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-10-01
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| Series: | CPT: Pharmacometrics & Systems Pharmacology |
| Online Access: | https://doi.org/10.1002/psp4.13022 |
| _version_ | 1797657213323444224 |
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| author | Shengyuan Zhang Akosua A. Agyeman Christoforos Hadjichrysanthou Joseph F. Standing |
| author_facet | Shengyuan Zhang Akosua A. Agyeman Christoforos Hadjichrysanthou Joseph F. Standing |
| author_sort | Shengyuan Zhang |
| collection | DOAJ |
| description | Abstract Mathematical models of viral dynamics have been reported to describe adequately the dynamic changes of severe acute respiratory syndrome‐coronavirus 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 tixagevimab‐cilgavimab, a monoclonal antibody combination which blocks infection of the target cells by neutralizing 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. |
| first_indexed | 2024-03-11T17:41:13Z |
| format | Article |
| id | doaj.art-c9c530d93ac94e078f655a3cba614082 |
| institution | Directory Open Access Journal |
| issn | 2163-8306 |
| language | English |
| last_indexed | 2024-03-11T17:41:13Z |
| publishDate | 2023-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | CPT: Pharmacometrics & Systems Pharmacology |
| spelling | doaj.art-c9c530d93ac94e078f655a3cba6140822023-10-18T10:22:39ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062023-10-0112101450146010.1002/psp4.13022SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapyShengyuan Zhang0Akosua A. Agyeman1Christoforos Hadjichrysanthou2Joseph F. Standing3Department of Pharmaceutics, School of Pharmacy University College London London UKInfection, Immunity and Inflammation Research and Teaching Department, Great Ormond Street Institute of Child Health University College London London UKDepartment of Mathematics University of Sussex Brighton UKInfection, Immunity and Inflammation Research and Teaching Department, Great Ormond Street Institute of Child Health University College London London UKAbstract Mathematical models of viral dynamics have been reported to describe adequately the dynamic changes of severe acute respiratory syndrome‐coronavirus 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 tixagevimab‐cilgavimab, a monoclonal antibody combination which blocks infection of the target cells by neutralizing 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.https://doi.org/10.1002/psp4.13022 |
| spellingShingle | Shengyuan Zhang Akosua A. Agyeman Christoforos Hadjichrysanthou Joseph F. Standing SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy CPT: Pharmacometrics & Systems Pharmacology |
| title | SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
| title_full | SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
| title_fullStr | SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
| title_full_unstemmed | SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
| title_short | SARS‐CoV‐2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
| title_sort | sars cov 2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy |
| url | https://doi.org/10.1002/psp4.13022 |
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