Artificial intelligence in vaccine development: applications, implementation, and future directions
- Author(s)
- Kumar, SN; Gondane, R; Mahindrakar, S; Vyawahare, S; Krishna, R; Subramaniam, S; Nair, BG; Kumar, GB; Madhavan, A; M, N; Babu, P;
- Journal Title
- Frontiers in Cellular and Infection Microbiology
- Publication Type
- Review
- Abstract
- Vaccination stands as one of the most transformative interventions in the history of human civilization. In medicine, vaccination stands as a cornerstone that has saved countless lives across generations. Nevertheless, conventional vaccine development remains encumbered by prolonged timelines, substantial financial investment, and high attrition rates particularly during late-stage clinical trials underscoring the urgent need for more efficient and systematic approaches. In recent years, artificial intelligence (AI) has emerged as a transformative force across the biomedical sciences, offering unprecedented computational capacity to process and interpret complex biological datasets. The convergence of AI with vaccinology represents a significant methodological advancement which has the potential to fundamentally redefine the vaccine development paradigm. AI integrates advances in machine learning, multi-omics data analysis, and high-performance computing to accelerate antigen discovery, epitope prediction, immunogen design, and clinical evaluation. This development represents a paradigm shift toward faster, more precise, and scalable strategies for vaccine development. This review critically examines the current landscape of AI applications in vaccine development, with particular emphasis on recent advancements, translational challenges, and the prospective role of AI in shaping the future of immunization science.
- Publisher
- Frontiers
- Keywords
- *Artificial Intelligence/trends; Humans; *Vaccine Development/methods/trends; *Vaccinology/methods/trends; *Vaccines/immunology; Machine Learning; Animals; Epitopes/immunology; antigen discovery; artificial intelligence (AI); epitope prediction; immunogen design; immunoinformatic; machine learning (ML); reverse vaccinology; structural vaccinology
- Department(s)
- Pathology
- Publisher's Version
- https://doi.org/10.3389/fcimb.2026.1870890
- Open Access at Publisher's Site
https://doi.org/10.3389/fcimb.2026.1870890- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2026-09-16 04:43:31
Last Modified: 2026-09-16 04:43:41