Evidence map›Paper›PMID 35338360›Full record

ReviewNature reviews. Genetics2022

Human organs-on-chips for disease modelling, drug development and personalized medicine.

Donald E Ingber

Open access · hybridAbstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 751 papers.

0numbers the graph read from it
0cells of the map it votes in
751citing papers in PubMed
95.2field-weighted citation impact, top 1% 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

751 citing papers in PubMed, 1,288 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Review
  10. RNA therapeutics: current status and future directions.Signal transduction and targeted therapy · 2026
    Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Leveraging Microphysiological Systems to Facilitate Neutrophil-Based Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  19. Article
  20. Review

691 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

1 author at 1 institution in 1 country.

Donald E IngberWyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA. don.ingber@wyss.harvard.edu.ORCID 0000-0002-4319-6520
Boston Children's Hospital · US

Funding

Lung-on-a-Chip Disease Models for Efficacy Testing (COVID-19 Competitive Revision)UH3HL141797 · NHLBI · HARVARD UNIVERSITY · PI INGBER, DONALD E · 2019 to 2021
$5.2M
6 · The paper itself

Abstract

The failure of animal models to predict therapeutic responses in humans is a major problem that also brings into question their use for basic research. Organ-on-a-chip (organ chip) microfluidic devices lined with living cells cultured under fluid flow can recapitulate organ-level physiology and pathophysiology with high fidelity. Here, I review how single and multiple human organ chip systems have been used to model complex diseases and rare genetic disorders, to study host-microbiome interactions, to recapitulate whole-body inter-organ physiology and to reproduce human clinical responses to drugs, radiation, toxins and infectious pathogens. I also address the challenges that must be overcome for organ chips to be accepted by the pharmaceutical industry and regulatory agencies, as well as discuss recent advances in the field. It is evident that the use of human organ chips instead of animal models for drug development and as living avatars for personalized medicine is ever closer to realization.

Indexed as

Lab-On-A-Chip DevicesPrecision MedicineAnimalsDrug DevelopmentHumansRare Diseases

Identifiers

PMID35338360
PMCPMC8951665
OpenAlexW4220652963

What OpenQuestion holds

Textmetadata
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.