Evidence map›Paper›PMID 33374802›Full record

ArticleVaccines2020

Resources, Production Scales and Time Required for Producing RNA Vaccines for the Global Pandemic Demand.

Zoltán Kis, Cleo Kontoravdi, Robin Shattock, Nilay Shah

Erratum issuedAbstract read
In one paragraph

Article in Vaccines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing 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

69 citing papers in PubMed.

  1. Trial
  2. IntegratedMolecular therapy. Nucleic acids · 2026
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9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Zoltán KisCentre for Process Systems Engineering, Department of Chemical Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK.ORCID 0000-0002-6598-8369
Cleo KontoravdiCentre for Process Systems Engineering, Department of Chemical Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK.ORCID 0000-0003-0213-4830
Robin ShattockDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London W2 1PG, UK.
Nilay ShahCentre for Process Systems Engineering, Department of Chemical Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK.

Funding

EPSRC EP/R013764/1UKRI EP/V01479X/1
6 · The paper itself

Abstract

To overcome pandemics, such as COVID-19, vaccines are urgently needed at very high volumes. Here we assess the techno-economic feasibility of producing RNA vaccines for the demand associated with a global vaccination campaign. Production process performance is assessed for three messenger RNA (mRNA) and one self-amplifying RNA (saRNA) vaccines, all currently under clinical development, as well as for a hypothetical next-generation saRNA vaccine. The impact of key process design and operation uncertainties on the performance of the production process was assessed. The RNA vaccine drug substance (DS) production rates, volumes and costs are mostly impacted by the RNA amount per vaccine dose and to a lesser extent by the scale and titre in the production process. The resources, production scale and speed required to meet global demand vary substantially in function of the RNA amount per dose. For lower dose saRNA vaccines, global demand can be met using a production process at a scale of below 10 L bioreactor working volume. Consequently, these small-scale processes require a low amount of resources to set up and operate. RNA DS production can be faster than fill-to-finish into multidose vials; hence the latter may constitute a bottleneck.

Indexed as

COVID-19mRNA vaccinespandemic-response vaccine productionproduction process modellingRNA vaccinessaRNA vaccinestechno-economic analysis

Identifiers

PMID33374802
PMCPMC7824664

What OpenQuestion holds

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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.