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

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.