Variability in antibody responses among individuals following vaccination is a universal phenomenon. So a well designed vaccine whose antigen should elicit a strong protective immune response in variety of individuals. Single-cell transcriptomics offers a potential avenue to understand the underlying mechanisms of these variations and improve our ability to evaluate and predict vaccine effectiveness that facilitates vaccine antigen design. Artificial intelligence tools make antigenic protein structure design more efficient and convenient than ever before. Based on the individual diversity of immune response characteristics revealed by single-cell sequencing results, we designed several antigenic variants of SARS-CoV-2, and ultimately verified that several mutant designs were able to efficiently provoke highly effective neutralizing antibodies to more than 11 Omicron variants, includes mutants that appear after the antigen has been designed. What’s more, the antigens we designed stimulated strong humoral and cellular immunity, with a neutralizing antibody titers of >1*10 4 at 28 days and a Th1-biased cellular immune response in BALB/C mice. And the result also indicates that the S–6P-GSAS variant elicits superior immunogenicity at lower doses compared to the S–2P variant.