Evidence map›Paper›PMID 37119028›Full record

ReviewMedicinal research reviews2023

Advanced models for respiratory disease and drug studies.

Jesus Shrestha, Keshav Raj Paudel, Hojjatollah Nazari, Vivek Dharwal, Sajad Razavi Bazaz, Matt D Johansen, Kamal Dua, Philip M Hansbro, Majid Ebrahimi Warkiani

Open access · hybridAbstract readReview
In one paragraph

Review in Medicinal research reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

10 citing papers in PubMed, 22 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Jesus ShresthaSchool of Biomedical Engineering, University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0003-3692-6676
Keshav Raj PaudelCentre for Inflammation, Centenary Institute and University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-3591-2080
Hojjatollah NazariSchool of Biomedical Engineering, University of Technology Sydney, Sydney, New South Wales, Australia.
Vivek DharwalCentre for Inflammation, Centenary Institute and University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-9645-3797
Sajad Razavi BazazSchool of Biomedical Engineering, University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-6419-3361
Matt D JohansenCentre for Inflammation, Centenary Institute and University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-5553-5270
Kamal DuaDiscipline of Pharmacy, Graduate School of Health, University of Technology, Sydney, New South Wales, Australia.ORCID 0000-0002-7507-1159
Philip M HansbroCentre for Inflammation, Centenary Institute and University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-4741-3035
Majid Ebrahimi WarkianiSchool of Biomedical Engineering, University of Technology Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-4184-1944
University of Technology Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global burden of respiratory diseases is enormous, with many millions of people suffering and dying prematurely every year. The global COVID-19 pandemic witnessed recently, along with increased air pollution and wildfire events, increases the urgency of identifying the most effective therapeutic measures to combat these diseases even further. Despite increasing expenditure and extensive collaborative efforts to identify and develop the most effective and safe treatments, the failure rates of drugs evaluated in human clinical trials are high. To reverse these trends and minimize the cost of drug development, ineffective drug candidates must be eliminated as early as possible by employing new, efficient, and accurate preclinical screening approaches. Animal models have been the mainstay of pulmonary research as they recapitulate the complex physiological processes, Multiorgan interplay, disease phenotypes of disease, and the pharmacokinetic behavior of drugs. Recently, the use of advanced culture technologies such as organoids and lung-on-a-chip models has gained increasing attention because of their potential to reproduce human diseased states and physiology, with clinically relevant responses to drugs and toxins. This review provides an overview of different animal models for studying respiratory diseases and evaluating drugs. We also highlight recent progress in cell culture technologies to advance integrated models and discuss current challenges and present future perspectives.

Indexed as

COVID-19PandemicsAnimalsDrug DevelopmentHumansanimal modelsdrug discoverylung-on-a-chipmedicinal researchrespiratory diseases

Identifiers

PMID37119028
PMCPMC10946967
OpenAlexW4367369628

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.