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A unifying model to explain frequent SARS-CoV-2 rebound after nirmatrelvir treatment and limited prophylactic efficacy

Author

Listed:
  • Shadisadat Esmaeili

    (Fred Hutchinson Cancer Center)

  • Katherine Owens

    (Fred Hutchinson Cancer Center)

  • Jessica Wagoner

    (University of Washington)

  • Stephen J. Polyak

    (University of Washington)

  • Judith M. White

    (University of Virginia)

  • Joshua T. Schiffer

    (Fred Hutchinson Cancer Center
    University of Washington)

Abstract

In a pivotal trial (EPIC-HR), a 5-day course of oral ritonavir-boosted nirmatrelvir, given early during symptomatic SARS-CoV-2 infection (within three days of symptoms onset), decreased hospitalization and death by 89.1% and nasal viral load by 0.87 log relative to placebo in high-risk individuals. Yet, nirmatrelvir/ritonavir failed as post-exposure prophylaxis in a trial, and frequent viral rebound has been observed in subsequent cohorts. We develop a mathematical model capturing viral-immune dynamics and nirmatrelvir pharmacokinetics that recapitulates viral loads from this and another clinical trial (PLATCOV). Our results suggest that nirmatrelvir’s in vivo potency is significantly lower than in vitro assays predict. According to our model, a maximally potent agent would reduce the viral load by approximately 3.5 logs relative to placebo at 5 days. The model identifies that earlier initiation and shorter treatment duration are key predictors of post-treatment rebound. Extension of treatment to 10 days for Omicron variant infection in vaccinated individuals, rather than increasing dose or dosing frequency, is predicted to lower the incidence of viral rebound significantly.

Suggested Citation

  • Shadisadat Esmaeili & Katherine Owens & Jessica Wagoner & Stephen J. Polyak & Judith M. White & Joshua T. Schiffer, 2024. "A unifying model to explain frequent SARS-CoV-2 rebound after nirmatrelvir treatment and limited prophylactic efficacy," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49458-9
    DOI: 10.1038/s41467-024-49458-9
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    References listed on IDEAS

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    1. Bryan T Mayer & Allan C deCamp & Yunda Huang & Joshua T Schiffer & Raphael Gottardo & Peter B Gilbert & Daniel B Reeves, 2022. "Optimizing clinical dosing of combination broadly neutralizing antibodies for HIV prevention," PLOS Computational Biology, Public Library of Science, vol. 18(4), pages 1-20, April.
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