Evidence map›Paper›PMID 34696222›Full record

ArticleVaccines2021

Use of Stability Modeling to Support Accelerated Vaccine Development and Supply.

Cristiana Campa, Thierry Pronce, Marilena Paludi, Jos Weusten, Laura Conway, James Savery, Christine Richards, Didier Clénet

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2021. 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
1.2field-weighted citation impact, top 21% 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, 28 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

8 authors at 5 institutions in 4 countries.

Cristiana CampaGSK, Technical R&D, 53100 Siena, Italy.
Thierry PronceGSK, Technical R&D, 1330 Rixensart, Belgium.
Marilena PaludiGSK, Technical R&D, 53100 Siena, Italy.
Jos WeustenMSD, Center for Mathematical Sciences, 5344 Oss, The Netherlands.
Laura ConwayMerck, Regulatory Affairs CMC Vaccines, North Wales, PA 19454, USA.
James SaveryAstraZeneca, Data Science & Modeling, BioPharmaceuticals Development, R&D, Cambridge 01223, UK.
Christine RichardsSanofi-Pasteur, Global Quality, Swiftwater, PA 18370, USA.
Didier ClénetSanofi-Pasteur, Bioprocess R&D Department, 69280 Marcy l'Etoile, France.
AstraZeneca (United Kingdom) · GBGlaxoSmithKline (Belgium) · BEInstitut Pasteur · FRMerck & Co., Inc., Rahway, NJ, USA (United States) · USSanofi (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stability assessment of pharmaceuticals in specific storage and shipment conditions is a key requirement to ensure that safe and efficacious products are administered to patients. This is particularly relevant for vaccines, with numerous vaccines strictly requiring cold storage to remain stable. When stability evaluation is exclusively based on real-time data, it may represent a bottleneck for rapid and effective vaccine access. Stability modeling for vaccines represents a key resource to predict stability based on accelerated stability studies; nevertheless, this approach is not fully exploited for these kinds of products. This is likely because of the complexity and diversity of vaccines, as well as the limited availability of dedicated guidelines or illustrative case studies. This article reports a cross-company perspective on stability modeling for vaccines. Several examples, based on the direct experience of the contributors, demonstrate that modeling approaches can be highly valuable to predict vaccines' shelf life and behavior during shipment or manipulation. It is demonstrated that modeling methodologies need to be tailored to the nature of the vaccine, the available prior knowledge, and the monitored attributes. Considering that the well-established strategies reported in ICH or WHO guidelines are not always broadly applicable to vaccines, this article represents an important source of information for vaccine researchers and manufacturers, setting the grounds for further discussion within the vaccine industry and with regulators.

Indexed as

accelerated predictive stabilityadvanced kinetic modelingCOVAX

Identifiers

PMID34696222
PMCPMC8539070
OpenAlexW3202970541

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.