Evidence map›Paper›PMID 38511587›Full record

ArticleAdvanced healthcare materials2024

High-Scale 3D-Bioprinting Platform for the Automated Production of Vascularized Organs-on-a-Chip.

Anna Fritschen, Nils Lindner, Sebastian Scholpp, Philipp Richthof, Jonas Dietz, Philipp Linke, Zeno Guttenberg, Andreas Blaeser

Open access · hybridAbstract read
In one paragraph

Article in Advanced healthcare materials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

13 citing papers in PubMed, 28 citations in OpenAlex.

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  5. Soft Micromanipulation Robot for Real-Time Adaptive Multimodal Operation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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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 1 institution in 1 country.

Anna FritschenBioMedical Printing Technology, Department of Mechanical Engineering, Technical University of Darmstadt, 64289, Darmstadt, Germany.ORCID 0000-0001-9114-8630
Nils LindnerBioMedical Printing Technology, Department of Mechanical Engineering, Technical University of Darmstadt, 64289, Darmstadt, Germany.ORCID 0000-0003-4220-8347
Sebastian ScholppBioMedical Printing Technology, Department of Mechanical Engineering, Technical University of Darmstadt, 64289, Darmstadt, Germany.ORCID 0009-0000-2390-3796
Philipp RichthofBioMedical Printing Technology, Department of Mechanical Engineering, Technical University of Darmstadt, 64289, Darmstadt, Germany.ORCID 0009-0006-2691-2894
Jonas DietzBioMedical Printing Technology, Department of Mechanical Engineering, Technical University of Darmstadt, 64289, Darmstadt, Germany.
Philipp Linkeibidi GmbH, Lochhamer Schlag 11, 82166, Gräfelfing, Germany.ORCID 0009-0000-9358-4137
Zeno Guttenbergibidi GmbH, Lochhamer Schlag 11, 82166, Gräfelfing, Germany.ORCID 0000-0001-6520-634X
Andreas BlaeserBioMedical Printing Technology, Department of Mechanical Engineering, Technical University of Darmstadt, 64289, Darmstadt, Germany.ORCID 0000-0003-3459-4268
Technische Universität Darmstadt · DE

Funding

German Federal Ministry for Economic Affairs and Energy (BMWi), AiF Projekt KK5031601CS0German federal state of Hesse, research cluster FlowForLife
6 · The paper itself

Abstract

3D bioprinting possesses the potential to revolutionize contemporary methodologies for fabricating tissue models employed in pharmaceutical research and experimental investigations. This is enhanced by combining bioprinting with advanced organs-on-a-chip (OOCs), which includes a complex arrangement of multiple cell types representing organ-specific cells, connective tissue, and vasculature. However, both OOCs and bioprinting so far demand a high degree of manual intervention, thereby impeding efficiency and inhibiting scalability to meet technological requirements. Through the combination of drop-on-demand bioprinting with robotic handling of microfluidic chips, a print procedure is achieved that is proficient in managing three distinct tissue models on a chip within only a minute, as well as capable of consecutively processing numerous OOCs without manual intervention. This process rests upon the development of a post-printing sealable microfluidic chip, that is compatible with different types of 3D-bioprinters and easily connected to a perfusion system. The capabilities of the automized bioprint process are showcased through the creation of a multicellular and vascularized liver carcinoma model on the chip. The process achieves full vascularization and stable microvascular network formation over 14 days of culture time, with pronounced spheroidal cell growth and albumin secretion of HepG2 serving as a representative cell model.

Indexed as

BioprintingLab-On-A-Chip DevicesPrinting, Three-DimensionalTissue EngineeringHep G2 CellsHumansNeovascularization, Physiologicbioprintingorgan‐on‐a‐chiproboticsvascularization

Identifiers

PMID38511587
PMCPMC11469029
OpenAlexW4393043894

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.