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Home›Model›Computer models help assess the effectiveness of drugs and vaccines against SARS-CoV-2

Computer models help assess the effectiveness of drugs and vaccines against SARS-CoV-2

By Levi Bailey
July 19, 2021
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Researchers are using computer models to simulate COVID-19 infections at the cellular level – the basic structural level of the human body.

The models allow virtual trials of drugs and vaccines, opening up the possibility of a pre-assessment of the efficacy of drugs and vaccines against the virus.

The University of Waterloo research team includes Anita Layton, professor of applied mathematics and holder of the Canada 150 Research Chair in Mathematical Biology and Medicine, and Mehrshad Sadria, doctoral student in applied mathematics.

The team uses “in silico” experiments to replicate how the human immune system processes the COVID-19 virus. In silico refers to tests located in the silicon of computer chips, as opposed to “in vitro” or “in vivo” experiments, located in test tubes or directly in living organisms.

“It’s not that in silico trials have to replace clinical trials,” Layton said. “A model is a simplification, but it can help us reduce drugs for clinical trials. Clinical trials are expensive and can cost human lives. The use of models allows the drug candidates to be restricted to those which are best for safety and efficacy.

The researchers, one of the first groups to work on these models, were able to capture the results of different treatments that have been used on COVID-19 patients in clinical trials. Their results are remarkably consistent with live data on COVID infections and treatments.

An example of a treatment used in the model was Remdesivir, a drug used in the World Health Organization’s global “solidarity” trials. Both the simulated model and the live trial showed the drug to be biologically effective but clinically questionable, unless it was administered soon after viral infection.

The model could also work for current and future variants of concern. Researchers predict that the virus will continue to mutate, which could precipitate new waves of infection.

“As we learn more about the different variants of concern, we may modify the structure or parameters of the model to simulate the interaction between the immune system and the variants,” Sadria said. “And then we can predict whether we should apply the same treatments or even how vaccines might work as well.”

Layton and Sadria are part of a new team, led by researchers at the University Health Network (UHN), which recently received a Rapid Response Grant from the Canadian Institutes of Health Research on COVID variants.

The UHN team will conduct experimental studies and modeling simulations to understand the spread of COVID variants in Canada.

Reference: Sadria M, Layton AT. Modeling the dynamics of SARS-CoV-2 infection within the host and potential treatments. Virus. 2021; 13 (6): 1141. do I: 10.3390 / v13061141

This article was republished from the following materials. Note: The material may have been modified for its length and content. For more information, please contact the cited source.



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