ReviewFrontiers in immunology2025
Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions.
Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- An integrated AI-driven vaccine design process: a systematic review of workflows from generative design to translational prediction.Immunologic research · 2026Pooled it
- Correlation does not equal causation: the imperative of causal inference in machine learning models for immunotherapy.Frontiers in immunology · 2025Pooled it
- Spatio-temporal forecasting of dengue in the Americas through hybrid mechanistic and data-driven models: Systematic review and meta-analysis.Infectious Disease Modelling · 2026Review
- Unleashing the immune arsenal: development of broad spectrum multiepitope bluetongue vaccine targeting conserved T cell epitopes of structural proteins.BMC genomics · 2026Article
- Large language models for bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Review
- In silico design and immunoinformatics assessment of a multiepitope vaccine targeting borealpox virus.Scientific reports · 2026Article
- Artificial intelligence in vaccine development: applications, implementation, and future directions.Frontiers in cellular and infection microbiology · 2026Review
- Vaccines for microbial eye diseases in the era of data science: opportunities and challenges.Frontiers in immunology · 2026Review
- Is the reverse vaccinology idea becoming exhausted?Frontiers in immunology · 2026Review
- Cross-protective efficacy of NA-based mRNA vaccine candidates against seasonal and avian influenza viruses.Frontiers in microbiology · 2026Article
- Integrating biocomputational techniques for vaccine development for glioblastoma multiforme: a possible way of enhancing precision.Frontiers in immunology · 2026Review
- Legal questions of AI-generated immunological products for infectious diseases.Human vaccines & immunotherapeutics · 2025Review
- From data to immunity: the role of machine learning in advancing malaria vaccine research: a scoping review.Tropical diseases, travel medicine and vaccines · 2025Review
- Reverse vaccinology-driven construction and bioinformatics validation of a multi-epitope vaccine against Brucella spp.Scientific reports · 2025Article
- Artificial intelligence and machine learning in the development of vaccines and immunotherapeutics-yesterday, today, and tomorrow.Frontiers in artificial intelligence · 2025Review
- Prediction of menstrual literacy among female university students using tree-based machine learning algorithms: A cross-sectional study in Bangladesh.Women's health (London, England)Article
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
The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.
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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 OpenQuestion graph.