Evidence map›Paper›PMID 37344503›Full record

ArticleScientific reports2023

A universal tool for stability predictions of biotherapeutics, vaccines and in vitro diagnostic products.

M Huelsmeyer, D Kuzman, M Bončina, J Martinez, C Steinbrugger, J Weusten, C Calero-Rubio, W Roche, B Niederhaus, Y VanHaelst and 11 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
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  11. Review
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  15. Article
  16. Fluorescence-Based Protein Stability Monitoring-A Review.International journal of molecular sciences · 2024
    Review
  17. 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

21 authors.

M HuelsmeyerDrug Product Development, AbbVie, Ludwigshafen, Germany.
D KuzmanBiologics Drug Product, Technical R&D, Global Drug Development, Novartis , Mengeš, Slovenia.
M BončinaBiologics Drug Product, Technical R&D, Global Drug Development, Novartis , Mengeš, Slovenia.
J MartinezR&D Immunoassays, Biomolecule Engineering - bioMAP, bioMérieux, Marcy L'étoile, France.
C SteinbruggerR&D Immunoassays, Biomolecule Engineering - bioMAP, bioMérieux, Marcy L'étoile, France.
J WeustenCenter for Mathematical Sciences, MSD, Oss, The Netherlands.
C Calero-RubioBiologics Drug Product Development & Manufacturing, Sanofi, Framingham, USA.
W RocheMSAT, Sanofi, Waterford, Ireland.
B NiederhausCMC-Biologics Statistics, Sanofi, Frankfurt, Germany.
Y VanHaelstCMC-Biologics Statistics, Sanofi, Gent, Germany.
M HrynykGlobal Drug Product Bioprocess Development, Sanofi, Toronto, Canada.
P BallestaAltran Technologies, Capgemini Engineering, Lyon, France.
H AchardAltran Technologies, Capgemini Engineering, Lyon, France.
S AugustoManufacturing Technology Department, Sanofi, Val-de-Reuil, France.
M GuilloisManufacturing Technology Department, Sanofi, Val-de-Reuil, France.
C PszczolinskiManufacturing Technology Department, Sanofi, Val-de-Reuil, France.
M GerasimovManufacturing Technology Department, Sanofi, Swiftwater, USA.
C NeyraManufacturing Technology Department, Sanofi, Swiftwater, USA.
D PonduriManufacturing Technology Department, Sanofi, Hyderabad, India.
S RameshManufacturing Technology Department, Sanofi, Hyderabad, India.
D ClénetGlobal Drug Product Bioprocess Development, Sanofi, Marcy L'étoile, France. Didier.Clenet@sanofi.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is of particular interest for biopharmaceutical companies developing and distributing fragile biomolecules to warrant the stability and activity of their products during long-term storage and shipment. In accordance with quality by design principles, advanced kinetic modeling (AKM) has been successfully used to predict long-term product shelf-life and relies on data from short-term accelerated stability studies that are used to generate Arrhenius-based kinetic models that can, in turn, be exploited for stability forecasts. The AKM methodology was evaluated through a cross-company perspective on stability modeling for key stability indicating attributes of different types of biotherapeutics, vaccines and biomolecules combined in in vitro diagnostic kits. It is demonstrated that stability predictions up to 3 years for products maintained under recommended storage conditions (2-8 °C) or for products that have experienced temperature excursions outside the cold-chain show excellent agreement with experimental real-time data, thus confirming AKM as a universal and reliable tool for stability predictions for a wide range of product types.

Indexed as

VaccinesDrug StabilityDrug StorageRefrigerationTemperatureVaccines

Identifiers

PMID37344503
PMCPMC10284933

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.