Predictive Modeling of Immune Escape and Antigenic Grouping of SARS-CoV-2 Variants

Nasir, A.; Lee, D.; Avena, L. E.; Montes Berrueta, D.; Speidel, T.; Wu, K.; Budigi, Y.; Carfi, A.; Stewart-Jones, G. B. E.; Edwards, D. K.

doi:10.1101/2025.05.28.656328

bioRxiv · 10.1101/2025.05.28.656328

Predictive Modeling of Immune Escape and Antigenic Grouping of SARS-CoV-2 Variants

Nasir, A.·Lee, D.·Avena, L. E.·Montes Berrueta, D.·Speidel, T.·Wu, K.·Budigi, Y.·Carfi, A.·Stewart-Jones, G. B. E.·Edwards, D. K.

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Abstract

The ongoing adaptive evolution of SARS-CoV-2 is characterized by the continued emergence of novel variants that escape from previously acquired infection- and/or vaccination-derived immunity. This continued SARS-CoV-2 variant evolution has necessitated annual vaccine updates to better match circulating viral variants. To optimize protection against emerging variants of interest and concern, a reliable means of predicting the immune escape of novel variants is needed to enable at-risk preparation of new vaccines. Herein, we describe the development and applications of a risk calculator that uses statistical modeling to predict the immune escape of emerging variants. The calculator utilizes previously published spike-antibody epitope and escape profiles and in vitro neutralization assessment of a large panel of pseudotyped SARS-CoV-2 variants evaluated against clinical sera. The calculator enables the grouping of antigenically related SARS-CoV-2 variants to guide strain selection for at-risk vaccine design and preparation, in anticipation of potential future requests by the global public health agencies. Here, we demonstrated the strain selection exercises for the XBB.1.5- and JN.1/KP.2-adapted mRNA-1273 COVID-19 vaccines in the 2023-2024 and 2024-2025 seasons, respectively, which were supported by both the risk calculator and preclinical and clinical immunogenicity data and were later recommended by the global public health agencies.

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Nasir, A., Lee, D., Avena, L. E., Montes Berrueta, D., Speidel, T., Wu, K., Budigi, Y., Carfi, A., Stewart-Jones, G. B. E., Edwards, D. K.. 2025-05-29. Predictive Modeling of Immune Escape and Antigenic Grouping of SARS-CoV-2 Variants. https://doi.org/10.1101/2025.05.28.656328

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