Temporary and spatial deposition of aerosol particles in the upper human airways during breathing cycle

Moskal, Arkadiusz; Gradoń, Leon

doi:10.1016/s0021-8502(02)00108-8

Cited by 58 publications

(31 citation statements)

References 10 publications

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“…Examples of numerical simulations for nanoparticle deposition include Asgharian and Anjilvel, 1 Bala´sha´zy and Hofmann, 4,5 Hofmann et al, 22 Kelly et al, 24 Moskal and Gradon, 36 Shi et al, 42 Xi and Longest, 50 Yu et al, 51,52 Zamankhan et al, 53 and Zhang and Kleinstreuer. 57 Almost all theoretical as well as experimental studies describing the mainly diffusional deposition in the tracheobronchial airways assumed uniform or parabolic inlet velocity profiles and particle distributions.…”

Section: Introductionmentioning

confidence: 99%

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

2008

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In order to achieve both manageable simulation and local accuracy of airflow and nanoparticle deposition in a representative human tracheobronchial (TB) region, the complex airway network was decomposed into adjustable triple-bifurcation units, spreading axially and laterally. Given Q(in) = 15 and 30 L/min and a realistic inlet velocity profile, the experimentally validated computer simulation model provided some interesting 3-D airflow patterns, i.e., for each TB-unit they depend on the upstream condition, local geometry and local Reynolds number. Directly coupled to the local airflow fields are the convective-diffusive transport and deposition of nanoparticles, i.e., 1 nm < or = d(p) < or = 100 nm. The CFD modeling predictions were compared to experimental observations as well as analytical modeling results. The CFD-simulated TB deposition values agree astonishingly well with analytical modeling results. However, measurable differences can be observed for bifurcation-by-bifurcation deposition fractions obtained with these two different approaches due to the effects of more realistic inlet conditions and geometric features incorporated in the CFD model. Specifically, while the difference between the total TB deposition fraction (DF) is less than 16%, it may be up to 70% for bifurcation-by-bifurcation DFs. In addition, it was found that fully developed flow and uniform nanoparticle concentrations can be assumed beyond generation G12. For nanoparticles with d(p) > 10 nm, the geometric effects, including daughter-branch rotation, are minor. Furthermore, the deposition efficiencies at each individual bifurcation in the TB region can be well correlated as a function of an effective diffusion parameter.

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Section: Introductionmentioning

confidence: 99%

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

2008

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“…It takes place, e.g. in the mouth (hard and soft palate), throat and at bifurcations of large bronchi (Moskal A. and Gradoń L., 2002;Sosnowski T.R. et al, 2007).…”

Section: Physics Of Aerosol Particle Flow and Deposition In The Respimentioning

confidence: 99%

“…It can be noted that the Brownian force acts on aerosol particles all the time but its direction and magnitude are randomly changed (through the random updating of value of Z) at the end of every time step ∆t. The presented method of numerical computations can be used to analyse particle motion in a human breathing system also at realistic non-steady-state flow conditions (Moskal A. and Gradoń L., 2002). Numerical solutions allow finding the trajectory of any particle of the defined size and properties, and eventually finding the place of particle deposition on the airway wall.…”

Section: Quantitative Models Of Deposition Of Inhaled Particlesmentioning

confidence: 99%

“…et al, 2004;Zhang Z. et al, 2005;Farkas A. and Balazhazy I., 2008;Ma B. and Lutchen K.R., 2009), which is an inaccurate simplification. Some studies show that particles in the realistic non-steady inhalation flow show dissimilar dynamics as compared to the constant flow conditions, and this leads to a different spatial distribution of particle deposition (Moskal A. and Gradoń L., 2002;Sosnowski T.R. et al, 2007).…”

Section: Aerosol Dynamics and Other Factors Influencing Particle Depomentioning

confidence: 99%

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Powder Particles and Technologies for Medicine Delivery to the Respiratory System: Challenges and Opportunities

Sosnowski¹

2018

KONA

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The paper discusses essential engineering challenges related to the application of powder medicines for pulmonary delivery as inhaled aerosol. Starting from a physically based description of the complexity of aerosol dynamics inside the respiratory system, the paper discusses several technical factors responsible for efficient drug delivery to the lungs: (i) interparticle interactions-which can be tuned by selection and control of powder manufacturing methods, (ii) inhaler design-as a determinant of flow dynamics through the inhaling device and degree of powder dispersion, (iii) the dynamics of inhalation in a given inhaler-which is related to patient-device interaction. Basic information on the standard (compendial) methods of the quantitative evaluation of dry powder inhalers (DPIs) are presented with a special focus on the correct data interpretation and the consequences for in vivo-in vitro correlation (IVIVC) problems. Some issues regarding the development of inhalation products (including generics) are also briefly highlighted. Finally, possible strategies of powder particle functionalization to obtain the required bioavailability are outlined on the basis of knowledge on the physicochemical interactions of inhaled particles with the lung fluids.

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“…denotes a pseudorandom vector (19). The amplitudes of the components of Brownian forces are thus computed at all time steps Δt, during the calculation of the particle trajectory.…”

Section: Theoretical and Numerical Modeling Particle Transport And DImentioning

confidence: 99%

Prediction of the Deposition of Dry Powder Aerosols

Mendes

Sousa

Pinto

2009

AAPS J

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Abstract. The trajectory, mass fluxes, and deposition of aerosolized particles in a complex tubular system have been predicted. A procedure based on Lagrangian stochastic modeling is proposed to enable the anticipation of such phenomena, taking advantage of experimental results to characterize the air flow. The predictions have been obtained for pharmaceutical aerosols delivered by dry powder inhalers. A critical assessment of the dispersion model has been carried out using data available in the literature. The procedure assumes a low volume fraction of particles in the simulation of turbulent dispersion, but deposition is physically based on the interaction between the particles and both solid and liquid surfaces. The results were confirmed by experimental tests of powder deposition, run according to the European Pharmacopoeia. A parametric study was also carried out with the aim of providing a more complete evaluation of the model's performance. The comparison between predictions and experimental results has shown that the model properly describes the deposition of aerosolized particles.KEY WORDS: aerosol; computational model; dry powder inhaler; lung drug delivery; particle deposition.

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Temporary and spatial deposition of aerosol particles in the upper human airways during breathing cycle

Cited by 58 publications

References 10 publications

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

Powder Particles and Technologies for Medicine Delivery to the Respiratory System: Challenges and Opportunities

Prediction of the Deposition of Dry Powder Aerosols

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