ReviewFrontiers in cellular and infection microbiology2026
Artificial intelligence in vaccine development: applications, implementation, and future directions.
Review in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.