Evidence map›Paper›PMID 42405958›Full record

ReviewHuman vaccines & immunotherapeutics2026

Next-generation vaccine adjuvants: Integrating nanotechnology, systems immunology, and computational approaches for precision vaccinology.

Tina Zarrinpanah, Maryam Mashhadi Abolghasem Shirazi, Seyed Mohammad Hasan Modarressi, Setareh Haghighat

Abstract readReview
In one paragraph

Review in Human vaccines & immunotherapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tina ZarrinpanahDepartment of Microbiology, Kish.C., Islamic Azad University, Kish, Iran.
Maryam Mashhadi Abolghasem ShiraziDepartment of Microbiology, TeMS.C., Islamic Azad University, Tehran, Iran.
Seyed Mohammad Hasan ModarressiDepartment of Pharmacology, TeMS.C., Islamic Azad University, Tehran, Iran.
Setareh HaghighatDepartment of Microbiology, TeMS.C., Islamic Azad University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccines based on purified antigens, recombinant proteins, and nucleic acid platforms increasingly depend on adjuvants to induce robust, durable, and appropriately polarized immune responses in humans. While classical adjuvants such as aluminum salts and oil-in-water emulsions have enabled the success of many licensed vaccines, their largely empirical design limits adaptability to emerging pathogens and population-specific needs. This review presents a translational framework for next-generation vaccine adjuvant development by integrating nanotechnology-based delivery systems, innate immune signaling mechanisms, and systems-level computational strategies relevant to human vaccination. We summarize the mechanisms and clinical relevance of licensed and advanced adjuvants, including alum, MF59, AS01/AS04, saponins, toll-like receptor agonists, and lipid nanoparticles, with emphasis on influenza, HPV, herpes zoster, and COVID-19 vaccines. By linking immunological mechanisms with delivery engineering and predictive modeling, this review highlights rational strategies to support safer and more effective human vaccines.

Indexed as

Adjuvants, ImmunologicAdjuvants, VaccineNanotechnologyVaccinesVaccinologyAnimalsCOVID-19 VaccinesHumansImmunity, InnateImmunoinformaticsNanoparticlesSystems BiologyVaccine DevelopmentAdjuvants, ImmunologicAdjuvants, VaccineCOVID-19 VaccinesVaccineshuman vaccinesinnate immune signalinglipid nanoparticlesnanotechnology-based delivery systemsprecision vaccinologysystems immunologyVaccine adjuvants

Identifiers

PMID42405958
PMCPMC13348964

What OpenQuestion holds

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Registered trials

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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.