Evidence mapPaperPMID 33801289Full record

ReviewBiomedicines2021

The Synergy between Organ-on-a-Chip and Artificial Intelligence for the Study of NAFLD: From Basic Science to Clinical Research.

Francesco De Chiara, Ainhoa Ferret-Miñana, Javier Ramón-Azcón

Open access · goldAbstract readReview
In one paragraph

Review in Biomedicines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 14% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Better In Vitro Tools for ExploringLife (Basel, Switzerland) · 2022
    Article
  13. Review
  14. Organ on Chip Technology to Model Cancer Growth and Metastasis.Bioengineering (Basel, Switzerland) · 2022
    Review
  15. Article
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

3 authors at 2 institutions in 1 country.

Francesco De ChiaraBiosensors for Bioengineering Group, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 10-12, 08028 Barcelona, Spain.ORCID 0000-0003-1537-1456
Ainhoa Ferret-MiñanaBiosensors for Bioengineering Group, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 10-12, 08028 Barcelona, Spain.ORCID 0000-0002-2254-2746
Javier Ramón-AzcónBiosensors for Bioengineering Group, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Baldiri I Reixac 10-12, 08028 Barcelona, Spain.ORCID 0000-0002-3636-8013
Institute for Bioengineering of Catalonia · ESInstitució Catalana de Recerca i Estudis Avançats · ES

Funding

Agència de Gestió d'Ajuts Universitaris i de Recerca 2019 LLAV 00056Centres de Recerca de Catalunya 2014- SGR-1460European Regional Development Fund 2014-2020European Research Council ERC-StG-DAMOC (714317)"la Caixa" Foundation project IBEC-La Caixa Healthy AgeingRetos de investigación: Proyectos I+D+i TEC2017-83716-C2-2-RSpanish Ministry of Economy and Competitiveness, through the "Severo Ochoa" Program SEV-2016-2019
6 · The paper itself

Abstract

Non-alcoholic fatty liver affects about 25% of global adult population. On the long-term, it is associated with extra-hepatic compliances, multiorgan failure, and death. Various invasive and non-invasive methods are employed for its diagnosis such as liver biopsies, CT scan, MRI, and numerous scoring systems. However, the lack of accuracy and reproducibility represents one of the biggest limitations of evaluating the effectiveness of drug candidates in clinical trials. Organ-on-chips (OOC) are emerging as a cost-effective tool to reproduce in vitro the main NAFLD's pathogenic features for drug screening purposes. Those platforms have reached a high degree of complexity that generate an unprecedented amount of both structured and unstructured data that outpaced our capacity to analyze the results. The addition of artificial intelligence (AI) layer for data analysis and interpretation enables those platforms to reach their full potential. Furthermore, the use of them do not require any ethic and legal regulation. In this review, we discuss the synergy between OOC and AI as one of the most promising ways to unveil potential therapeutic targets as well as the complex mechanism(s) underlying NAFLD.

Indexed as

artificial intelligenceextra-hepatic outcomeNAFLDorgan-on-a-chip

Identifiers

PMID33801289
PMCPMC7999375
OpenAlexW3135706894

What Socratic 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 Socratic graph.