Cited by 1,1853D Printing in Biomedical ResearchMicrofluidic and Capillary Electrophoresis ApplicationsTissue Engineering and Regenerative Medicine

Organs-on-chips at the frontiers of drug discovery

Open access
Esch, Eric W., Bahinski, Anthony, Huh, Dongeun·2015·Nature Reviews Drug Discovery

Abstract

Improving the effectiveness of preclinical predictions of human drug responses is critical to reducing costly failures in clinical trials. Recent advances in cell biology, microfabrication and microfluidics have enabled the development of microengineered models of the functional units of human organs - known as organs-on-chips - that could provide the basis for preclinical assays with greater predictive power. Here, we examine the new opportunities for the application of organ-on-chip technologies in a range of areas in preclinical drug discovery, such as target identification and validation, target-based screening, and phenotypic screening. We also discuss emerging drug discovery opportunities enabled by organs-on-chips, as well as important challenges in realizing the full potential of this technology.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nrd4539

Cites

104 of 104 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Organ-on-chip systems have shown promise sustaining functional microtissues for relatively extended timeframes.

    “Recently, organ-on-chip systems—microphysiological systems that combine the use of microfluidics, tissue engineering, and microfabrication tools—have shown promise sustaining functional microtissues for relatively extended timeframes [9,10,11,12].”

    From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [10]

    The ‘Comparison with conventional models’ section says organs-on-chips can reconstitute organ-level physiological functions, supporting the functional-microtissue part of the claim. But the passages do not establish that this function is sustained for relatively extended periods; ‘Current challenges and limitations’ instead describes long-term culture as a major challenge. Page numbers are not available in our copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • The lung-on-a-chip system was also used as a model for lung diseases such as pulmonary edema.

    “C: the system was also used as a model for lung diseases like pulmonary edema.”

    From Modeling physiological events in 2D vs. 3D cell culture (2017) · cites this paper as [33]

  • A lung-on-a-chip system was able to recreate organ-level functions, including an inflammatory response to bacteria.

    “B: the system could recreate organ-level functions, such as an inflammatory response bacteria.”

    From Modeling physiological events in 2D vs. 3D cell culture (2017) · cites this paper as [33]

  • 3D tissue models, such as in vitro tissue-engineered disease models, have shown promise for overcoming obstacles faced with 2D cultured cells and animal models.

    “3D tissue models, such as in vitro tissue-engineered disease models have shown promise for addressing the current obstacles faced with 2D in vitro cultured cells and animal models [352–356].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Esch, E. W., Bahinski, A., & Huh, D.
Affiliations
  • University of Pennsylvania (US)
  • Harvard University (US)
Corresponding author
Huh, Dongeun
Venue
Nature Reviews Drug Discovery
Published
2015-03-20
Volume
14
Issue
4
Pages
248-260
ISSN
  • 1474-1776 (ISSN-L)
  • 1474-1784
OpenAlex
W2010546163
Cited by
1,185
References
104
Citations by year
2026: 57 · 2025: 88 · 2024: 74 · 2023: 87 · 2022: 107 · 2021: 124 · 2020: 114 · 2019: 133 · 2018: 134 · 2017: 151 · 2016: 94 · 2015: 19 · 2014: 1 · 2012: 1
FWCI
10.26
Type
journal article
Language
en
Open access
Locations
  • Nature Reviews Drug Discovery (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Heart, Lung, and Blood Institute (DP2HL127720)
  • National Institute of Environmental Health Sciences (P30ES013508)
  • National Center for Chronic Disease Prevention and Health Promotion (1DP2HL127720-01)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
  • Physical Sciences › Engineering › Biomedical Engineering › Microfluidic and Capillary Electrophoresis Applications
  • Health Sciences › Medicine › Surgery › Tissue Engineering and Regenerative Medicine
Keywords
organ-on-a-chip, drug discovery, preclinical drug screening, toxicity screening, target identification and validation, target-based screening, phenotypic screening, microfluidics, microfabrication, stratified medicine, predictive preclinical models
MeSH terms
Animals, Computer Simulation, Drug Industry, Drug Evaluation, Preclinical, Humans, Models, Biological, Pharmacokinetics, Rare Diseases, Drug Discovery, High-Throughput Screening Assays

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review