Exploring the Therapeutic Potential of Defective Interfering Particles in Reducing the Replication of SARS-CoV-2

Macauley Locke, Dmitry Grebennikov, Igor Sazonov, Martín López-García, Marina Loguinova, Andreas Meyerhans, Gennady Bocharov () and Carmen Molina-París ()
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Macauley Locke: Department of Applied Mathematics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK
Dmitry Grebennikov: Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, 119333 Moscow, Russia
Igor Sazonov: Faculty of Science and Engineering, Swansea University, Swansea SA1 8EN, UK
Martín López-García: Department of Applied Mathematics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK
Marina Loguinova: The National Medical Research Centre for Endocrinology, 117292 Moscow, Russia
Andreas Meyerhans: Infection Biology Laboratory, Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, 08003 Barcelona, Spain
Gennady Bocharov: Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, 119333 Moscow, Russia
Carmen Molina-París: Department of Applied Mathematics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK

Mathematics, 2024, vol. 12, issue 12, 1-28

Abstract: SARS-CoV-2 still presents a global threat to human health due to the continued emergence of new strains and waning immunity among vaccinated populations. Therefore, it is still relevant to investigate potential therapeutics, such as therapeutic interfering particles (TIPs). Mathematical and computational modeling are valuable tools to study viral infection dynamics for predictive analysis. Here, we expand on the previous work on SARS-CoV-2 intra-cellular replication dynamics to include defective interfering particles (DIPs) as potential therapeutic agents. We formulate a deterministic model that describes the replication of wild-type (WT) SARS-CoV-2 virus in the presence of DIPs. Sensitivity analysis of parameters to several model outputs is employed to inform us on those parameters to be carefully calibrated from experimental data. We then study the effects of co-infection on WT replication and how DIP dose perturbs the release of WT viral particles. Furthermore, we provide a stochastic formulation of the model that is compared to the deterministic one. These models could be further developed into population-level models or used to guide the development and dose of TIPs.

Keywords: mathematical model; virus replication dynamics; sensitivity; SARS-CoV-2; defective interfering particles (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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