Evidence map›Paper›PMID 40236275›Full record

ArticleEngineering in life sciences2025

Automation of a Capillary-Wave Microbioreactor Platform to Enhance Phage Sensitivity Screen Efficiency.

Kevin Viebrock, Ilka Knoke, Leon Huß, Detlev Rasch, Sven Meinen, Andreas Dietzel, Rainer Krull

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kevin ViebrockInstitute of Biochemical Engineering Technische Universität Braunschweig Braunschweig Germany.ORCID https://orcid.org/0000-0003-3315-1983
Ilka KnokeInstitute of Biochemical Engineering Technische Universität Braunschweig Braunschweig Germany.
Leon HußInstitute of Biochemical Engineering Technische Universität Braunschweig Braunschweig Germany.
Detlev RaschInstitute of Biochemical Engineering Technische Universität Braunschweig Braunschweig Germany.
Sven MeinenCenter of Pharmaceutical Engineering Technische Universität Braunschweig Braunschweig Germany.
Andreas DietzelCenter of Pharmaceutical Engineering Technische Universität Braunschweig Braunschweig Germany.
Rainer KrullInstitute of Biochemical Engineering Technische Universität Braunschweig Braunschweig Germany.ORCID https://orcid.org/0000-0003-2821-8610

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To increase their throughput, reduce laboratory work and improve reproducibility, automation of bioprocesses is gaining in importance nowadays. This applies in particular to microbioreactors (MBRs), which can be easily integrated in highly parallelized and automated platforms and, therefore, be applied for screenings, cell-based assays, and bioprocess development. One promising pharmaceutical application for MBRs is the performance of phage sensitivity tests called phagograms in phage therapy. However, there is no automated and parallelized platform available so far that fulfills the requirements of phagograms. Therefore, a novel highly parallelizable capillary-wave microbioreactor (cwMBR) with a volume of 7 µL, which has already been successfully applied for phagograms, was extended by an in-house built platform for automated fluid addition in the single-digit nanoliter range. The cwMBR has a phage-repellent hydrophilic glass surface. Furthermore, a custom-made highly parallelizable device for biomass measurement in the lower microliter scale was developed and validated in the cwMBR. To prove the applicability of the platform for the generation of phagograms, a phagogram using

Indexed as

automationmicrobioreactorsnanodispenserparallelizationphagograms

Identifiers

PMID40236275
PMCPMC11997256

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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.