Evidence map›Paper›PMID 35232251›Full record

ReviewOpen biology2022

Studying metabolism with multi-organ chips: new tools for disease modelling, pharmacokinetics and pharmacodynamics.

Tanvi Shroff, Kehinde Aina, Christian Maass, Madalena Cipriano, Joeri Lambrecht, Frank Tacke, Alexander Mosig, Peter Loskill

Abstract readReview
In one paragraph

Review in Open biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Review
  2. Environmental science & technology · 2026
    Review
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  4. Article
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  16. Strategies for optimization of hypoglycemia rat models.Animal models and experimental medicine · 2025
    Review
  17. Article
  18. Review
  19. Review
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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.

Tanvi ShroffNMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany.ORCID 0000-0002-2118-0608
Kehinde AinaInstitute of Biochemistry II, Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany.
Christian MaassesqLABS GmbH, Saterland, Germany.ORCID 0000-0001-7618-0421
Madalena CiprianoDepartment for Microphysiological Systems, Institute for Biomedical Engineering, Faculty of Medicine, Eberhard Karls University Tübingen, Österbergstraße 3, 72074 Tübingen, Germany.ORCID 0000-0002-6285-3434
Joeri LambrechtDepartment of Hepatology and Gastroenterology, Charité University Medicine Berlin, Campus Virchow Klinikum and Campus Charité Mitte, Berlin, Germany.
Frank TackeDepartment of Hepatology and Gastroenterology, Charité University Medicine Berlin, Campus Virchow Klinikum and Campus Charité Mitte, Berlin, Germany.ORCID 0000-0001-6206-0226
Alexander MosigInstitute of Biochemistry II, Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany.ORCID 0000-0002-5687-2444
Peter LoskillNMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany.ORCID 0000-0002-5000-0581

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-clinical models to study metabolism including animal models and cell assays are often limited in terms of species translatability and predictability of human biology. This field urgently requires a push towards more physiologically accurate recapitulations of drug interactions and disease progression in the body. Organ-on-chip systems, specifically multi-organ chips (MOCs), are an emerging technology that is well suited to providing a species-specific platform to study the various types of metabolism (glucose, lipid, protein and drug) by recreating organ-level function. This review provides a resource for scientists aiming to study human metabolism by providing an overview of MOCs recapitulating aspects of metabolism, by addressing the technical aspects of MOC development and by providing guidelines for correlation with

Indexed as

Lab-On-A-Chip DevicesModels, BiologicalAnimalsComputer Simulationdisease modellingin silico modellingin vitro to in vivo translationmetabolismmulti-organchipPK/PD

Identifiers

PMID35232251
PMCPMC8889168

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.