SARS-CoV-2 viral dynamic modelling to inform model selection and timing and efficacy of antiviral therapy.
Shengyuan ZhangAkosua A AgyemanChristoforos HadjichrysanthouJoseph F StandingPublished in: CPT: pharmacometrics & systems pharmacology (2023)
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.
Keyphrases
- sars cov
- clinical trial
- induced apoptosis
- respiratory syndrome coronavirus
- immune response
- monoclonal antibody
- electronic health record
- big data
- systematic review
- newly diagnosed
- randomized controlled trial
- oxidative stress
- study protocol
- stem cells
- healthcare
- type diabetes
- phase ii
- dendritic cells
- prognostic factors
- metabolic syndrome
- skeletal muscle
- endoplasmic reticulum stress
- signaling pathway
- insulin resistance
- double blind
- weight loss
- combination therapy
- smoking cessation
- phase iii