Evidence map›Paper›PMID 35236838›Full record

ArticleNPJ vaccines2022

Pandemic-response adenoviral vector and RNA vaccine manufacturing.

Zoltán Kis, Kyungjae Tak, Dauda Ibrahim, Maria M Papathanasiou, Benoît Chachuat, Nilay Shah, Cleo Kontoravdi

Open access · goldAbstract read
In one paragraph

Article in NPJ vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
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

22 citing papers in PubMed, 32 citations in OpenAlex.

  1. IntegratedMolecular therapy. Nucleic acids · 2026
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  16. Anion exchange HPLC monitoring of mRNAFrontiers in molecular biosciences · 2024
    Article
  17. Review
  18. Article
  19. Article
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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

7 authors at 1 institution in 1 country.

Zoltán Kis *The Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK. z.kis@sheffield.ac.uk.ORCID http://orcid.org/0000-0002-6598-8369
Kyungjae Tak *The Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Dauda IbrahimThe Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Maria M PapathanasiouThe Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Benoît ChachuatThe Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.ORCID http://orcid.org/0000-0003-4780-9686
Nilay ShahThe Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Cleo KontoravdiThe Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK. cleo.kontoravdi98@imperial.ac.uk.ORCID http://orcid.org/0000-0003-0213-4830
Imperial College London · GB

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/R013756/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/R013764/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/V01479X/1
6 · The paper itself

Abstract

Rapid global COVID-19 pandemic response by mass vaccination is currently limited by the rate of vaccine manufacturing. This study presents a techno-economic feasibility assessment and comparison of three vaccine production platform technologies deployed during the COVID-19 pandemic: (1) adenovirus-vectored (AVV) vaccines, (2) messenger RNA (mRNA) vaccines, and (3) the newer self-amplifying RNA (saRNA) vaccines. Besides assessing the baseline performance of the production process, impact of key design and operational uncertainties on the productivity and cost performance of these vaccine platforms is quantified using variance-based global sensitivity analysis. Cost and resource requirement projections are computed for manufacturing multi-billion vaccine doses for covering the current global demand shortage and for providing annual booster immunisations. The model-based assessment provides key insights to policymakers and vaccine manufacturers for risk analysis, asset utilisation, directions for future technology improvements and future epidemic/pandemic preparedness, given the disease-agnostic nature of these vaccine production platforms.

Identifiers

PMID35236838
PMCPMC8891260
OpenAlexW4220668654

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.