Evidence map›Paper›PMID 28774561›Full record

ReviewVaccine2018

Personalized vaccinology: A review.

G A Poland, I G Ovsyannikova, R B Kennedy

Registry-linked trialAbstract readReview
In one paragraph

Review in Vaccine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04625725 (A Phase III Randomized, Double-blind, Placebo-controlled, Multi-center Study in Adults to Determine the Safety and Efficacy of AZD7442, a Combination Product of Two Monoclonal Antibodies), which is not on this map. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
–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.

NCT04625725 phase3completednot on this mapstarted 2020, after this paper: background citation

A Phase III Randomized, Double-blind, Placebo-controlled, Multi-center Study in Adults to Determine the Safety and Efficacy of AZD7442, a Combination Product of Two Monoclonal Antibodies (AZD8895 and AZD1061), for Pre-exposure Prophylaxis of COVID-19.

TypeinterventionalSponsorAstraZenecaRan2020 to 2023Enrolled5,197ConditionsCOVID-19ArmsAZD7442, Placebo
3 · Its place in the literature

Who cites it

100 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. The Progress of Active Immunotherapy for Parkinson's Disease.International journal of molecular sciences · 2026
    Review
  8. Article
  9. Review
  10. Immunosenescence and susceptibility to respiratory viruses: a state-of-the-art review.European respiratory review : an official journal of the European Respiratory Society · 2026
    Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. COVID-19 vaccination status and factors associated with deaths from the disease, Vitória, 2020-2023: cross-sectional study.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2025
    Article
  19. Article
  20. Observational

40 more citing papers are in PubMed but not listed here.

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

3 authors.

G A PolandMayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: poland.gregory@mayo.edu.
I G OvsyannikovaMayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, MN 55905, USA.
R B KennedyMayo Clinic Vaccine Research Group, Mayo Clinic, Rochester, MN 55905, USA.

Funding

Bioinformatics Approach to Influenza A/H1N1 Vaccine Immune ProfilingU01AI089859 · NIAID · MAYO CLINIC ROCHESTER · PI POLAND, GREGORY A. · 2010 to 2015
$33.8M
The Immunogenetics of Measles ImmunityR01AI033144 · NIAID · MAYO CLINIC ROCHESTER · PI POLAND, GREGORY A. · 1993 to 2022
$8.1M
Immunogenetic Mechanisms of Vaccine ResponseR37AI048793 · NIAID · MAYO CLINIC ROCHESTER · PI POLAND, GREGORY A. · 2011 to 2020
$5.4M
Systems Biology of Mumps Vaccine ResponseR01AI138965 · NIAID · MAYO CLINIC ROCHESTER · PI KENNEDY, RICHARD B · 2018 to 2022
$3.9M
Transcriptomic Signatures of Influenza Vaccine ResponsesR01AI132348 · NIAID · MAYO CLINIC ROCHESTER · PI KENNEDY, RICHARD B, POLAND, GREGORY A. · 2018 to 2022
$3.9M
Understanding measles vaccine failure (and success) in Southern IndiaR01AI121054 · NIAID · MAYO CLINIC ROCHESTER · PI JACOB, JOSHY, KENNEDY, RICHARD B · 2017 to 2021
$3.8M
Genetic Markers of Long-Term Mumps Vaccine ImmunityR01AI127365 · NIAID · MAYO CLINIC ROCHESTER · PI KENNEDY, RICHARD B · 2016 to 2020
$3.6M
NCEZID CDC HHS U50 CK000431NIAID NIH HHS N01 AI040065NIAID NIH HHS R01 AI033144NIAID NIH HHS R01 AI121054NIAID NIH HHS R01 AI127365NIAID NIH HHS R01 AI132348NIAID NIH HHS R01 AI138965NIAID NIH HHS R37 AI048793NIAID NIH HHS U01 AI089859
6 · The paper itself

Abstract

At the current time, the field of vaccinology remains empirical in many respects. Vaccine development, vaccine immunogenicity, and vaccine efficacy have, for the most part, historically been driven by an empiric "isolate-inactivate-inject" paradigm. In turn, a population-level public health paradigm of "the same dose for everyone for every disease" model has been the normative thinking in regard to prevention of vaccine-preventable infectious diseases. In addition, up until recently, no vaccines had been designed specifically to overcome the immunosenescence of aging, consistent with a post-WWII mentality of developing vaccines and vaccine programs for children. It is now recognized that the current lack of knowledge concerning how immune responses to vaccines are generated is a critical barrier to understanding poor vaccine responses in the elderly and in immunoimmaturity, discovery of new correlates of vaccine immunogenicity (vaccine response biomarkers), and a directed approach to new vaccine development. The new fields of vaccinomics and adversomics provide models that permit global profiling of the innate, humoral, and cellular immune responses integrated at a systems biology level. This has advanced the science beyond that of reductionist scientific approaches by revealing novel interactions between and within the immune system and other biological systems (beyond transcriptional level), which are critical to developing "downstream" adaptive humoral and cellular responses to infectious pathogens and vaccines. Others have applied systems level approaches to the study of antibody responses (a.k.a. "systems serology"), [1] high-dimensional cell subset immunophenotyping through CyTOF, [2,3] and vaccine induced metabolic changes [4]. In turn, this knowledge is being utilized to better understand the following: identifying who is at risk for which infections; the level of risk that exists regarding poor immunogenicity and/or serious adverse events; and the type or dose of vaccine needed to fully protect an individual. In toto, such approaches allow for a personalized approach to the practice of vaccinology, analogous to the substantial inroads that individualized medicine is playing in other fields of human health and medicine. Herein we briefly review the field of vaccinomics, adversomics, and personalized vaccinology.

Indexed as

HumansImmunity, CellularImmunity, HumoralImmunity, InnatePrecision MedicineSystems BiologyVaccinesVaccinesAdaptiveCellular immunityHumoral immunityImmunityImmunizationImmunogeneticsInnate immunityVaccinationVaccines

Identifiers

PMID28774561
PMCPMC5792371

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.