Evidence map›Paper›PMID 39678160›Full record

ArticleJournal of aerosol science2025

Subject-Specific Multi-Scale Modeling of the Fate of Inhaled Aerosols.

A P Kuprat, Y Feng, R A Corley, C Darquenne

Abstract read
In one paragraph

Article in Journal of aerosol science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

A P KupratPacific Northwest National Laboratory, Richland, WA, USA.
Y FengSchool of Chemical Engineering, Oklahoma State University, Stillwater, OK, USA.
R A CorleyGreek Creek Toxicokinetics Consulting, LLC, Boise, ID, USA.
C DarquenneDepartment of Medicine, University of California, San Diego, CA, USA.

Funding

Multiscale Modeling of Lung Disease-Influenced Aerosol DosimetryU01ES028669 · NIEHS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DARQUENNE, CHANTAL · 2018 to 2022
$3.3M
NIEHS NIH HHS U01 ES028669
6 · The paper itself

Abstract

Determining the fate of inhaled aerosols in the respiratory system is essential in assessing the potential toxicity of inhaled airborne materials, responses to airborne pathogens, or in improving inhaled drug delivery. The availability of high-resolution clinical lung imaging and advances in the reconstruction of lung airways from CT images have led to the development of subject-specific in-silico 3D models of aerosol dosimetry, often referred to as computational fluid-particle-dynamics (CFPD) models. As CFPD models require extensive computing resources, they are typically confined to the upper and large airways. These models can be combined with lower-dimensional models to form multiscale models that predict the transport and deposition of inhaled aerosols in the entire respiratory tract. Understanding where aerosols deposit is only the first of potentially several key events necessary to predict an outcome, being a detrimental health effect or a therapeutic response. To that end, multiscale approaches that combine CFPD with physiologically-based pharmacokinetics (PBPK) models have been developed to evaluate the absorption, distribution, metabolism, and excretion (ADME) of toxic or medicinal chemicals in one or more compartments of the human body. CFPD models can also be combined with host cell dynamics (HCD) models to assess regional immune system responses. This paper reviews the state of the art of these different multiscale approaches and discusses the potential role of personalized or subject-specific modeling in respiratory health.

Indexed as

aerosol dosimetrycomputational fluid particle dynamics (CFPD)host cell dynamics (HCD)multi-scale modelingphysiologically-based pharmacokinetics (PBPK)subject-specific modeling

Identifiers

PMID39678160
PMCPMC11636312

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.