Paxlovid is an extremely effective antiviral directed against SARS-CoV-2 which reduced hospitalisation by 90% in a seminal clinical trial. However, in community cohorts, paxlovid is associated with frequent viral and symptomatic rebound. Paxlovid is also not efficacious as post-exposure prophylaxis and did not reduce duration of symptoms in a follow up trial. To explain these discordant results, Dr Schiffer and his team developed a mathematical model and fit this model to detailed viral load data from two trials. In this presentation, Dr Schiffer will discuss how the model identified mechanisms underlying viral rebound and strategies to avoid this outcome. He will briefly describe efforts to model other antivirals and will conclude by touching on early work to identify immunologic predictors of COVID-19 severity.
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Joshua T Schiffer, MD Joshua T Schiffer, MD is an infectious diseases physician specialising in cancer and infections. He runs a research group focused on mathematical modelling of various human viral pathogens including SARS-CoV-2, HIV, HSV-2, CMV, HHV6, Ebola and influenza. His group’s work synthesizes concepts from multiple disciplines including virology, immunology, pharmacology, epidemiology, mathematics, statistics, ecology, and evolutionary biology. |
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