Evidence map›Paper›PMID 36071354›Full record

ReviewPharmaceutical research2022

Advancements in Particle Engineering for Inhalation Delivery of Small Molecules and Biotherapeutics.

Rachel Yoon Kyung Chang, Hak-Kim Chan

Abstract readReview
In one paragraph

Review in Pharmaceutical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–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

28 citing papers in PubMed.

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  14. Inhalable nanoparticle-based drug delivery system for non-small cell lung cancer therapy: promises and challenges.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025
    Review
  15. Review
  16. Article
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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

2 authors.

Rachel Yoon Kyung ChangAdvanced Drug Delivery Group, Faculty of Medicine and Health, Sydney Pharmacy School, The University of Sydney, S341, Pharmacy and Bank Building A15, Sydney, New South Wales, 2006, Australia.
Hak-Kim ChanAdvanced Drug Delivery Group, Faculty of Medicine and Health, Sydney Pharmacy School, The University of Sydney, S341, Pharmacy and Bank Building A15, Sydney, New South Wales, 2006, Australia. kim.chan@sydney.edu.au.ORCID http://orcid.org/0000-0002-7054-3137

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dry powder inhalation formulations have become increasingly popular for local and systemic delivery of small molecules and biotherapeutics. Powder formulations provide distinct advantages over liquid formulations such as elimination of cold chain due to room temperature stability, improved portability, and the potential for increasing patient adherence. To become a viable product, it is essential to develop formulations that are stable (physically, chemically and/or biologically) and inhalable over the shelf-life. Physical particulate properties such as particle size, morphology and density, as well as chemical properties can significantly impact aerosol performance of the powder. This review will cover these critical attributes that can be engineered to enhance the dispersibility of inhalation powder formulations. Challenges in particle engineering for biotherapeutics will be assessed, followed by formulation strategies for overcoming the hurdles. Finally, the review will discuss recent examples of successful dry powder biotherapeutic formulations for inhalation delivery that have been clinically assessed.

Indexed as

Dry Powder InhalersAdministration, InhalationAerosolsHumansParticle SizePowdersAerosolsPowdersbiologicsdry powder formulationinhalationparticle engineeringsmall molecules

Identifiers

PMID36071354
PMCPMC9451127

What OpenQuestion holds

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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.