Evidence map›Paper›PMID 39789401›Full record

ReviewMolecular biotechnology2026

A Bibliometric Analysis on Multi-epitope Vaccine Development Against SARS-CoV-2: Current Status, Development, and Future Directions.

Kanwal Khalid, Fiaz Ahmad, Ayaz Anwar, Seng-Kai Ong

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Towards precision epitopes based vaccine againstBiochemistry and biophysics reports · 2025
    Article
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.

Kanwal KhalidCentre for Virus and Vaccine Research, School of Medical and Life Sciences, Sunway University, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia. kanwalkhalid8@gmail.com.ORCID http://orcid.org/0000-0003-4486-3097
Fiaz AhmadDepartment of Economics and Finance, Sunway Business School, Sunway University, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia.
Ayaz AnwarDepartment of Biological Sciences, School of Medical and Life Sciences, Sunway University, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia.
Seng-Kai OngDepartment of Biological Sciences, School of Medical and Life Sciences, Sunway University, Bandar Sunway, 47500, Petaling Jaya, Selangor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The etiological agent for the coronavirus disease 2019 (COVID-19), the SARS-CoV-2, caused a global pandemic. Although mRNA, viral-vectored, DNA, and recombinant protein vaccine candidates were effective against the SARS-CoV-2 Wuhan strain, the emergence of SARS-CoV-2 variants of concern (VOCs) reduced the protective efficacies of these vaccines. This necessitates the need for effective and accelerated vaccine development against mutated VOCs. The development of multi-epitope vaccines against SARS-CoV-2 based on in silico identification of highly conserved and immunogenic epitopes is a promising strategy for future SARS-CoV-2 vaccine development. Considering the evolving landscape of the COVID-19 pandemic, we have conducted a bibliometric analysis to consolidate current findings and research trends in multi-epitope vaccine development to provide insights for future vaccine development strategies. Analysis of 102 publications on multi-epitope vaccine development against SARS-CoV-2 revealed significant growth and global collaboration, with India leading in the number of publications, along with an identification of the most prolific authors. Key journals included the Journal of Biomolecular Structure and Dynamics, while top collaborations involved Pakistan-China and India-USA. Keyword analysis showed a prominent focus on immunoinformatics, epitope prediction, and spike glycoprotein. Advances in immunoinformatics, including AI-driven epitope prediction, offer promising avenues for the development of safe and effective multi-epitope vaccines. Immunogenicity may be further improved through nanoparticle-based systems or the use of adjuvants along with real-time genomic surveillance to tailor vaccines against emerging variants.

Indexed as

BibliometricsCOVID-19 VaccinesEpitopesSARS-CoV-2Vaccine DevelopmentViral VaccinesCOVID-19HumansPandemicsCOVID-19 VaccinesEpitopesViral VaccinesBibliometric analysisCOVID-19Multi-epitopeMultiepitopeSARS-CoV-2

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.