Evidence map›Paper›PMID 40271119›Full record

ArticleEngineering in life sciences2025

Influenza A Virus Production Following Quality by Design Principles.

Tilia Zinnecker, Kristin Thiele, Timo Schmidberger, Yvonne Genzel, Udo Reichl

Abstract read
In one paragraph

Article in Engineering in life sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Tilia ZinneckerMax Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany.ORCID https://orcid.org/0009-0008-9514-3069
Kristin ThieleSartorius Stedim Cellca GmbH Ulm Germany.
Timo SchmidbergerSartorius Stedim Biotech GmbH Göttingen Germany.
Yvonne GenzelMax Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany.ORCID https://orcid.org/0000-0002-2652-5943
Udo ReichlMax Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany.ORCID https://orcid.org/0000-0001-6538-1332

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Establishing manufacturing processes for cell culture-based pharmaceutical products involves managing multiple parameters that can affect yield and efficiency, as well as process robustness and product quality. Implementing Quality by Design (QbD) principles can support process optimization, while streamlining the chemistry, manufacturing, and control aspects for regulatory approval. In this study, we mimic a QbD approach based on an influenza A virus production process using two clonal suspension Madin-Darby canine kidney (MDCK) cell lines with distinct characteristics. We performed a quantitative risk assessment including biological and technical parameters to identify the Critical Process Parameters (CPPs). To comprehensively study the effects and interactions of four CPPs, we used an Ambr 15 scale-down system following a Design of Experiments (DoE) approach. After data analysis and modeling, we obtained design spaces characterized by high robustness with a less than 1% risk of failure and even some indications for virus titer and yield improvement, while keeping process-related impurities such as DNA and total protein concentration low. These findings were subsequently verified at a more than 100-fold higher working volume. Taken together, our approach may stimulate ideas for the implementation of streamlined process development and regulatory approval in the field of viral vaccine production.

Indexed as

Ambr 15cell cultureDesign of Experimentsinfluenza A virusprocess developmentQuality by Design

Identifiers

PMID40271119
PMCPMC12016631

What OpenQuestion holds

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LicenceCC BY
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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.