Evidence map›Paper›PMID 28795174›Full record

ReviewLab on a chip2017

Tissue chips - innovative tools for drug development and disease modeling.

L A Low, D A Tagle

Abstract readReview
In one paragraph

Review in Lab on a chip, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 1 pooled it
–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

70 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Advances in Engineering Human Tissue Models.Frontiers in bioengineering and biotechnology · 2020
    Pooled it
  2. Trial
  3. Article
  4. Review
  5. Review
  6. Review
  7. Tissue chips as headway model and incitement technology.Synthetic and systems biotechnology · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Progress and application of lung-on-a-chip for lung cancer.Frontiers in bioengineering and biotechnology · 2024
    Review
  18. Review
  19. Review
  20. Type-Independent 3D Writing and Nano-Patterning of Confined Biopolymers.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article

10 more citing papers are in PubMed but not listed here.

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

2 authors.

L A LowNational Center for Advancing Translational Sciences, National Institutes of Health, 6701 Democracy Boulevard, Bethesda, MD 20892, USA. danilo.tagle@nih.gov.
D A Tagle

Funding

Intramural NIH HHS Z99 TR999999
6 · The paper itself

Abstract

The high rate of failure during drug development is well-known, however recent advances in tissue engineering and microfabrication have contributed to the development of microphysiological systems (MPS), or 'organs-on-chips' that recapitulate the function of human organs. These 'tissue chips' could be utilized for drug screening and safety testing to potentially transform the early stages of the drug development process. They can also be used to model disease states, providing new tools for the understanding of disease mechanisms and pathologies, and assessing effectiveness of new therapies. In the future, they could be used to test new treatments and therapeutics in populations - via clinical trials-on-chips - and individuals, paving the way for precision medicine. Here we will discuss the wide-ranging and promising future of tissue chips, as well as challenges facing their development.

Indexed as

Drug DiscoveryLab-On-A-Chip DevicesModels, BiologicalTissue EngineeringAnimalsBiomedical ResearchHumansMicrofluidic Analytical Techniques

Identifiers

PMID28795174
PMCPMC5621042

What OpenQuestion holds

Textmetadata
LicenceTDM
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.