ReviewPharmaceutics2021
Flow and Particle Modelling of Dry Powder Inhalers: Methodologies, Recent Development and Emerging Applications.
Review in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed, 36 citations in OpenAlex.
- Prediction of site-specific drug deposition via dry powder inhaler using non-invasive real-time particle emission signal monitoring system.Frontiers in pharmacology · 2026Article
- Charged Particle Dynamics in Dry Powder Inhalers.Molecular pharmaceutics · 2025Article
- Biopolymeric Inhalable Dry Powders for Pulmonary Drug Delivery.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Leveraging Numerical Simulation Technology to Advance Drug Preparation: A Comprehensive Review of Application Scenarios and Cases.Pharmaceutics · 2024Review
- Numerical Modeling of Particle Dynamics Inside a Dry Powder Inhaler.Pharmaceutics · 2022Article
- A CFD-DEM investigation of powder transport and aerosolization in ELLIPTA® dry powder inhaler.Powder technology · 2022Article
- Effects of dose loading conditions and device geometry on the transport and aerosolization in dry powder inhalers: A simulation study.International journal of pharmaceutics · 2021Article
- Comparative Assessment of In Vitro and In Silico Methods for Aerodynamic Characterization of Powders for Inhalation.Pharmaceutics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
Abstract
Dry powder inhaler (DPI) is a device used to deliver a drug in dry powder form to the lungs. A wide range of DPI products is currently available, with the choice of DPI device largely depending on the dose, dosing frequency and powder properties of formulations. Computational fluid dynamics (CFD), together with various particle motion modelling tools, such as discrete particle methods (DPM) and discrete element methods (DEM), have been increasingly used to optimise DPI design by revealing the details of flow patterns, particle trajectories, de-agglomerations and depositions within the device and the delivery paths. This review article focuses on the development of the modelling methodologies of flow and particle behaviours in DPI devices and their applications to device design in several emerging fields. Various modelling methods, including the most recent multi-scale approaches, are covered and the latest simulation studies of different devices are summarised and critically assessed. The potential and effectiveness of the modelling tools in optimising designs of emerging DPI devices are specifically discussed, such as those with the features of high-dose, pediatric patient compatibility and independency of patients' inhalation manoeuvres. Lastly, we summarise the challenges that remain to be addressed in DPI-related fluid and particle modelling and provide our thoughts on future research direction in this field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.