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A SARS-CoV-2 variant‑adjusted threshold of protection model for monoclonal antibody pre-exposure prophylaxis against COVID-19

Author

Listed:
  • Rhiannon Edge

    (AstraZeneca)

  • Sam Matthews

    (AstraZeneca)

  • Bahar Ahani

    (AstraZeneca)

  • Anastasia A. Aksyuk

    (AstraZeneca)

  • Lindsay Clegg

    (AstraZeneca)

  • John L. Perez

    (AstraZeneca)

  • Mark T. Esser

    (AstraZeneca)

  • Lee-Jah Chang

    (AstraZeneca)

  • Ian Hirsch

    (AstraZeneca)

  • Tonya Villafana

    (AstraZeneca)

  • John Pura

    (AstraZeneca)

  • Oleg Stepanov

    (AstraZeneca)

  • Katie Streicher

    (AstraZeneca)

  • Tom White

    (AstraZeneca)

  • Taylor S. Cohen

    (AstraZeneca)

  • Dean Follmann

    (National Institutes of Health)

  • Peter B. Gilbert

    (Fred Hutchinson Cancer Center)

  • Seth Seegobin

    (AstraZeneca)

Abstract

Clinical development of monoclonal antibodies (mAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is challenging due to rapid changes in the variant landscape. This study identified a threshold model for neutralising antibody (nAb) titres associated with clinically relevant protection against symptomatic COVID-19 for vulnerable populations. Using efficacy data from the phase 3 PROVENT pre-exposure prophylaxis trial of tixagevimab–cilgavimab (NCT04625725), individual nAb ID50 titres were predicted by dividing serum mAb concentration by prevalence-adjusted tixagevimab–cilgavimab potency (from in vitro IC50 values combined with viral surveillance data) and related to efficacy with a Cox model. The Threshold of Protection (ToP) Cox model was externally validated using data from the phase 3 SUPERNOVA trial (NCT05648110), which assessed sipavibart efficacy against symptomatic COVID-19 in immunocompromised participants. The PROVENT ToP model estimated the variant-specific observed efficacies from SUPERNOVA for 3 and 6 months post any dose with Lin’s concordance of 0.86 and 0.75, respectively. This approach integrates predicted nAb ID50 titres against multiple SARS-CoV-2 variants into a ToP model that can be applied across different variants and could serve as a surrogate endpoint in immunobridging studies to expedite clinical evaluation and regulatory approval for mAbs targeting SARS-CoV-2.

Suggested Citation

  • Rhiannon Edge & Sam Matthews & Bahar Ahani & Anastasia A. Aksyuk & Lindsay Clegg & John L. Perez & Mark T. Esser & Lee-Jah Chang & Ian Hirsch & Tonya Villafana & John Pura & Oleg Stepanov & Katie Stre, 2025. "A SARS-CoV-2 variant‑adjusted threshold of protection model for monoclonal antibody pre-exposure prophylaxis against COVID-19," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63972-4
    DOI: 10.1038/s41467-025-63972-4
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    References listed on IDEAS

    as
    1. Eva Stadler & Martin T. Burgess & Timothy E. Schlub & Shanchita R. Khan & Khai Li Chai & Zoe K. McQuilten & Erica M. Wood & Mark N. Polizzotto & Stephen J. Kent & Deborah Cromer & Miles P. Davenport &, 2023. "Monoclonal antibody levels and protection from COVID-19," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    2. Dean Follmann & Meagan P. O’Brien & Jonathan Fintzi & Michael P. Fay & David Montefiori & Allyson Mateja & Gary A. Herman & Andrea T. Hooper & Kenneth C. Turner & Kuo- Chen Chan & Eduardo Forleo-Neto , 2023. "Examining protective effects of SARS-CoV-2 neutralizing antibodies after vaccination or monoclonal antibody administration," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
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