Challenges and Progress of Computer Simulation in Aiding Modern Vaccine Development

OBJECTIVE  To explore the core challenges faced by traditional vaccine development, analyze the application value and specific practices of computer simulation technology in addressing these challenges and optimizing the vaccine research and development(R&D) process, and provide theoretical references and methodological support for modern vaccine R&D.

METHODS  Combined with recent representative vaccine cases approved by the U.S. Food and Drug Administration and Chinese regulatory authorities, this study systematically reviews the specific strategies and application paths of computer simulation technologies(including molecular docking, artificial intelligence/machine learning, systems biology, and multi-omics integration) in key links of vaccine R&D, such as vaccine antigen screening and design, adjuvant development and optimization, as well as prediction of immunogenicity and protective efficacy.

RESULTS  Computer simulation technology could significantly shorten the vaccine R&D cycle, improve the accuracy of candidate antigen and adjuvant screening, enhance the ability to respond to rapidly mutating pathogens, and provide data support for quality control in vaccine production and the development of detection methods. Practical vaccine cases showed that this technology can effectively improve vaccine protection rates, optimize immunization procedures, and promote the design of broad-spectrum vaccines.

CONCLUSION  Computer simulation has become the core support for the transformation of modern vaccine R&D from “experience-driven” to “data-model dual-driven”. However, its application is still restricted by bottlenecks such as uneven data quality, limited cross-species extrapolation ability of models, and delays in closed-loop iteration. In the future, it is necessary to further strengthen “computation-experiment” collaboration through multi-source data integration, development of interpretable artificial intelligence models, and construction of automated experimental platforms, so as to provide more accurate and efficient vaccine R&D solutions for responding to viral mutations and emerging infectious diseases.