<![CDATA[Adjuvants play a crucial role in modern vaccine formulations by enhancing immune responses, prolonging protection, and reducing the required antigen dose. Although several adjuvants have been globally licensed, the development of novel adjuvants still faces major challenges such as unpredictable immunogenicity, potential toxicity, and high in vivo testing costs. In silico approaches offer promising solutions for accelerating adjuvant design and validation in a more efficient and targeted manner. This review summarizes recent advances in computational methods for adjuvant development, including epitope prediction, molecular docking, molecular dynamics simulation, and the application of artificial intelligence. It also discusses currently licensed adjuvants and highlights case studies involving in silico-designed immune-receptor agonists such as Toll-like-receptor (TLR) ligands. Integrating empirical and bioinformatic strategies is expected to create new opportunities for developing safer, more specific, and personalized vaccine adjuvants. Key challenges and future research directions are also identified to optimize the incorporation of in silico approaches into global vaccine innovation.]]>
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