Computer model simulates COVID infection, and treatment

Researchers in Canada have built a computer model that replicates how the human immune system interacts with the COVID-19 virus, and can predict whether drugs or vaccines will have an impact on the infection.

The team from the University of Waterloo in Ontario say the “in silico” model could be used as a pre-screening tool to give an initial indication of whether a medicine has potential for COVID-19 before companies embark on a clinical testing programme.

The researchers – led by professor of applied mathematics Anita Layton – said they are one of the first groups to be working on this type of sophisticated model, which is described in the journal Viruses.

“It’s not that in-silico trials should replace clinical trials,” said Layton. “Clinical trials are expensive and can cost human lives. Using models helps narrow the drug candidates to the ones that are best for safety and efficacy.”

The platform was able to predict the results of different treatments that have already been tested on COVID-19 patients in clinical trials – including Gilead Sciences’ antiviral Veklury (remdesivir) – with “remarkable” consistency, according to the scientists.

The model and the actual trials of the drug both showed that it was “biologically effective but clinically questionable, unless administered shortly after viral infection,” they said.

They also pitted the model against convalescent plasma therapy – which ultimately generated disappointing results in trials – and an experimental therapy designed to block entry of the SARS-CoV-2 virus into host cells.

Layton and Mehrshad Sadria, an applied mathematics PhD student, reckon the in-silico model will still be valid even for future variants of SARS-CoV-2, and could be modified easily to accommodate other coronaviruses.

“The availability of SARS-CoV-2 vaccines is a relief for many,” they write in the paper. “Nevertheless, the virus has undergone and will continue to undergo mutation [and] SARS-CoV-2 is almost surely not the last novel coronavirus we must battle.”

Layton and Sadria are part of a new team, led by researchers at the University Health Network (UHN), that in March was granted C$14 million (around $11 million) in funding by the Canadian Institutes of Health Research (CIHR) to study COVID variants of concern.

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

“As we learn more about different variants of concern, we can change the model’s structure or parameters to simulate the interaction between the immune system and the variants,” commented Sadria.

“And we can then predict if we should apply the same treatments or even how the vaccines might work as well,” he said.

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