Computationally efficient analysis of particle transport and deposition in a human whole-lung-airway model. Part I: Theory and model validation

Improved aerosol deposition predictions in human upper respiratory tract using coupled mesh phantom-based computational model

Aerosol deposition in the human respiratory tract significantly impacts drug delivery, pollutant exposure, and radiological protection. While existing models, such as the Multiple-Path Particle Dosimetry (MPPD) and the Human Respiratory Tract Model (HRTM) from International Commission on Radiological Protection (ICRP) provide valuable insights, their reliance on simplified geometries and flow dynamics, limits their ability to accurately predict particle deposition within realistic anatomies. This study integrates Mesh-type Reference Computational Phantoms (MRCPs) with computational fluid-particle dynamics (CFPD) to address these limitations. Our simulations reveal the influence of complex anatomical features, including nasal cavity, trachea, and bronchial regions, on aerosol deposition patterns. For ambient aerosol particles in the diffusion-dominated regime (< 0.5 μm), CFPD results reveal enhanced nasal deposition fractions than ICRP predictions, while, above this size, the ICRP semi-empirical model shows overestimations. In the extrathoracic (ET) airways, deposition distribution varied significantly between ET1 and ET2, with ET2 receiving 65-75% of deposits (near the junction of ET1 and ET2) under certain flow conditions. In the bronchial bifurcation (BB1), deposition efficiency varies with Stokes number and Reynolds number, revealing localized preferential deposition. These findings enhance our understanding of aerosol behaviour and paves the way for more accurate therapeutic and safety models in radiological protection.

Ultrafine particles: Sources, toxicity, and deposition dynamics in the human respiratory tract -- experimental and computational approaches

Ultrafine particles (UFPs ≤ 100 nm) pose significant health risks, including respiratory and cardiovascular diseases, and cancer. This review consolidates main sources, toxicity, and exposure assessment approaches to elucidate the deposition dynamics of UFPswithin the human respiratory tract. Key factors influencing the deposition fraction (DF) are highlighted. Our findings indicate that the DF surpasses 50% for particles ≤50 nm and reaches up to 70% for particles ≤30 nm, impacting both adults and children. Vulnerable populations, such as children and individuals with pre-existing health conditions, are disproportionately affected, yet research focusing on these groups remains scarce. Methodological deficiencies, including high costs, simplifying assumptions, and computational constraints, challenge prediction accuracy. Experimental methods struggle to capture temporal fluctuations, while computational models fail to account for complex phenomena. Addressing these gaps is crucial for refining public health regulations and advancing nanomedicine. An improved understanding of UFPs dynamics will enhance protective measures and nanomedicine applications, particularly in targeted drug delivery and diagnostics. This review emphasizes the need for innovative experimental and computational methods to study UFPs deposition dynamics, ultimately advancing our understanding of UFPs' impact on human health.

Engineering nanoliposomal tiotropium bromide embedded in a lactose-arginine carrier forming Trojan-particle dry powders for efficient pulmonary drug delivery: A combined approach of in vitro-3D printing and in silico-CFD modeling

Nanocarrier-based dry powders for lung disease treatment are crucial, with in vitro and in silico research being pivotal to their success. This study introduces a method for creating Tiotropium-bromide liposomal inhalation dry powder, termed "Trojan-particles," utilizing thin-film hydration and spray-drying with lactose-arginine carriers. Encapsulating tiotropium-bromide in nanoliposomes enhances lung treatment via liposomes' unique features. This formulation was examined through in vitro-3D-printing and in silico-CFD analysis. Nanoliposomes and powder were evaluated for physicochemical attributes, aerosolization, encapsulation-efficiency (EE%), and release. Both liposomes (90 nm) and powder particles (3 µm) were spherical. Liposomes had an EE% over 95 % and a zeta-potential of -28.3 mV. The optimal formulation was tested in vitro at 30, 60, and 90 L/min using a 3D-printed airway replica. CFD analysis evaluated particle deposition in steady and realistic inhalation with monodisperse and polydisperse particles. Based on realistic airway geometry, model utilized k-ω-SST turbulence model for the continuous phase and Lagrangian-DEM for the discrete phase, analyzed through ANSYS Fluent. The 20 %-arginine nanoliposomal-tiotropium formulation outperformed others due to arginine's dispersibility and therapeutic benefits, including nitric oxide conversion. The formulation competes with commercial dry powders due to its chemical, biochemical advantages, and Trojan-based physical traits, reducing exhalation risk. Simulation data aligned with experimental findings, showing that higher inhalation flows increase particle deposition in airways due to greater inertia and turbulence. At 60 L/min, the polydisperse model matched experimental data better than the monodisperse model. Alongside improving dry powder performance via a nanoliposomal formulation, this research highlights the development of a novel CFD method for their assessment.

Experimental Full-volume Airway Approximation for Assessing Breath-dependent Regional Aerosol Deposition

Modeling aerosol dynamics in the airways is challenging, and most modern personalized in vitro tools consider only a single inhalation maneuver through less than 10% of the total lung volume. Here, we present an in vitro modeling pipeline to produce a device that preserves patient-specific upper airways while approximating deeper airways, capable of achieving total lung volumes over 7 liters. The modular system, called TIDAL, includes tunable inhalation and exhalation breathing capabilities with resting flow rates up to 30 liters per minute. We show that the TIDAL system is easily coupled with industrially and clinically relevant devices for aerosol therapeutics. Using a vibrating mesh nebulizer, we report central-to-peripheral (C:P) aerosol deposition measurements aligned with both in vivo and in silico benchmarks. These findings underscore the effectiveness of the TIDAL model in predicting airway deposition dynamics for inhalable therapeutics.

Leveraging Numerical Simulation Technology to Advance Drug Preparation: A Comprehensive Review of Application Scenarios and Cases

BACKGROUND/OBJECTIVES

Numerical simulation plays an important role in pharmaceutical preparation recently. Mechanistic models, as a type of numerical model, are widely used in the study of pharmaceutical preparations. Mechanistic models are based on a priori knowledge, i.e., laws of physics, chemistry, and biology. However, due to interdisciplinary reasons, pharmacy researchers have greater difficulties in using computer models.

METHODS

In this paper, we highlight the application scenarios and examples of mechanistic modelling in pharmacy research and provide a reference for drug researchers to get started.

RESULTS

By establishing a suitable model and inputting preparation parameters, researchers can analyze the drug preparation process. Therefore, mechanistic models are effective tools to optimize the preparation parameters and predict potential quality problems of the product. With product quality parameters as the ultimate goal, the experiment design is optimized by mechanistic models. This process emphasizes the concept of quality by design.

CONCLUSIONS

The use of numerical simulation saves experimental cost and time, and speeds up the experimental process. In pharmacy experiments, part of the physical information and the change processes are difficult to obtain, such as the mechanical phenomena during tablet compression and the airflow details in the nasal cavity. Therefore, it is necessary to predict the information and guide the formulation with the help of mechanistic models.

Assessing respiratory airflow unsteadiness under different tidal respiratory frequencies using large eddy simulation method

Unsteady respiratory airflow characteristics play a crucial role in understanding the deposition of toxic particles and inhaled aerosol drugs in the human respiratory tract. Considering the variations in respiratory flow rate and glottis motion under different respiratory frequencies, these respiratory airflow characteristics are studied by large-eddy simulations, including pressure field, power loss, modal spatial patterns, and vortex structures. Firstly, the results reveal that varying respiratory frequencies significantly affect airflow unsteadiness, turbulent evolution, and vortex structure dissipation, as they increase the complexity and butterfly effect introduced by the turbulent disturbance. Secondly, the pressure drops and flow rate at the glottis also conform to a power-law relationship considering the respiratory physiological characteristics, especially under low respiratory frequencies. Glottis motion plays different roles in energy consumption during inspiration and expiration, and its magnitude can be predicted using a polynomial function based on glottis area and respiratory flowrate under different respiratory frequencies. Finally, modal decomposition can be effectively applied to the study of respiratory flow characteristics, but we recommend separately studying the inspiration and expiration. The spatial distribution of the dominant mode characterizes the majority of respiratory flow characteristics and are influenced by respiratory frequency. Spectral entropy results indicate that glottis motion and slow breathing both delay the transitions in the upper respiratory tract during inspiration and expiration. These results confirm that the respiratory physiology characteristics under different respiratory frequencies have a significant impact on the unsteady respiratory airflow characteristics and warrant further study.

The utility of hybrid in silico models of airflow and aerosol dosimetry in the lung

The development and application of multi-scale models of the lung has significantly increased in recent years. These hybrid models merge realistic representations of the larger airways with lower-dimensional descriptions of the bronchioles and respiratory airways. Due to recent advancements, it is possible to calculate airflow and dosimetry throughout the entire lung, enabling model validation with human or animal data. Here, we present a hybrid modeling pipeline and corresponding characteristic airflow and particle deposition hotspots. Next, we discuss the limitations of current hybrid models, including the need to update lower-dimensional deposition function descriptions to better represent realistic airway geometries. Future directions should include modeling diseased lungs and use of machine learning to predict whole lung dosimetry maps for a wider population.

Engineering innovations in medicine and biology: Revolutionizing patient care through mechanical solutions

The overlap between mechanical engineering and medicine is expanding more and more over the years. Engineers are now using their expertise to design and create functional biomaterials and are continually collaborating with physicians to improve patient health. In this review, we explore the state of scientific knowledge in the areas of biomaterials, biomechanics, nanomechanics, and computational fluid dynamics (CFD) in relation to the pharmaceutical and medical industry. Focusing on current research and breakthroughs, we provide an overview of how these fields are being used to create new technologies for medical treatments of human patients. Barriers and constraints in these fields, as well as ways to overcome them, are also described in this review. Finally, the potential for future advances in biomaterials to fundamentally change the current approach to medicine and biology is also discussed.

Development of an effective two-equation turbulence modeling approach for simulating aerosol deposition across a range of turbulence levels

Pharmaceutical aerosol systems present a significant challenge to computational fluid dynamics (CFD) modeling based on the need to capture multiple levels of turbulence, frequent transition between laminar and turbulent flows, anisotropic turbulent particle dispersion, and near-wall particle transport phenomena often within geometrically complex systems over multiple time scales. Two-equation turbulence models, such as the k - ω family of approximations, offer a computationally efficient solution approach, but are known to require the use of near-wall (NW) corrections and eddy interaction model (EIM) modifications for accurate predictions of aerosol deposition. The objective of this study was to develop an efficient and effective two-equation turbulence modeling approach that enables accurate predictions of pharmaceutical aerosol deposition across a range of turbulence levels. Key systems considered were the traditional aerosol deposition benchmark cases of a 90-degree bend (R e = 6,000 ) and a vertical straight section of pipe (R e = 10,000 ), as well as a highly complex case of direct-to-infant (D2I) nose-to-lung pharmaceutical aerosol delivery from an air-jet dry powder inhaler (DPI) including a patient interface and infant nasal geometry through mid-trachea (500 < R e < 7,000 ). Of the k - ω family of models, the low Reynolds number (LRN) shear stress transport (SST) approach was determined to provide the best agreement with experimental aerosol deposition data in the D2I system, based on an improved simulation of turbulent jet flow that frequently occurs in DPIs. Considering NW corrections, a new correlation was developed to quantitatively predict best regional values of the y + l i m i t , within which anisotropic NW turbulence is approximated. Considering EIM modifications, a previously described drift correction approach was implemented in pharmaceutical aerosol simulations for the first time. Considering all model corrections and modifications applied to the D2I system, regional relative errors in deposition fractions between CFD predictions and new experimental data were improved from 19-207% (no modifications) to 2-15% (all modifications) with a notable decrease in computational time (up to ∼15%). In conclusion, the highly efficient two-equation k - ω models with physically realistic corrections and modifications provided a viable, efficient and accurate approach to simulate the transport and deposition of pharmaceutical aerosols in complex airway systems that include laminar, turbulent and transitional flows.

Automated bidirectional coupling of multiscale models of aerosol dosimetry: validation with subject-specific deposition data

Assessing the toxicity of airborne particulate matter or the efficacy of inhaled drug depends upon accurate estimates of deposited fraction of inhaled materials. In silico approaches can provide important insights into site- or airway-specific deposition of inhaled aerosols in the respiratory system. In this study, we improved on our recently developed 3D/1D model that simulate aerosol transport and deposition in the whole lung over multiple breath cycles (J. Aerosol Sci 151:105647). A subject-specific multiscale lung model of a healthy male subject using computational fluid-particle dynamics (CFPD) in a 3D model of the oral cavity through the large bronchial airways entering each lobe was bidirectionally coupled with a recently improved Multiple Path Particle Dosimetry (MPPD) model to predict aerosol deposition over the entire respiratory tract over multiple breaths for four conditions matching experimental aerosol exposures in the same subject from which the model was developed. These include two particle sizes (1 and 2.9 μm) and two subject-specific breathing rates of ~300 ml/s (slow breathing) and ~750 ml/s (fast breathing) at a target tidal volume of 1 L. In silico predictions of retained fraction were 0.31 and 0.29 for 1 μm and 0.66 and 0.62 for 2.9 μm during slow and fast breathing, respectively, and compared well with experimental data (1 μm: 0.31±0.01 (slow) and 0.27±0.01 (fast), 2.9 μm: 0.63±0.03 (slow) and 0.68±0.02 (fast)). These results provide a great deal of confidence in the validity and reliability of our approach.

Numerical investigations of the micro lunar dust particles deposition in the human oral respiratory airway

Understanding the deposition of lunar dust (LD) particles in the human respiratory system is of great significance for protecting astronauts' health from the toxicity of lunar dust. A Euler-Lagrangian approach is adopted to track the LD particle motion in a human oral airway model. The investigations are conducted considering different inspiration rates and micro-particle sizes as well as different abnormal pressures and abnormal temperatures. It is found that 1) almost all the LD particles tend to enter the right lung rather than the left lung, especially in the upper right lobe; 2) at lower ambient pressure, fewer LD particles will deposit in the upper airway, while more particles will enter the lung; 3) at lower temperature, more LD particles are deposited in the upper airway, while fewer are deposited in the lung. In summary, the present work has shown that the LD particles have different depositing properties in the upper airway and the lung lobe regions up to the particle size, inspiration flow rate, temperature and pressure. It should pay more attentions on the upper airway and right upper lobe when it studies the toxicity of the lunar dust, and can't ignore the impact of the environmental temperature and pressure.

The simulation of the emission of iron fumes caused by shielded metal arc welding using a computational fluid dynamics method

Computational fluid dynamics (CFD) is an indispensable simulation tool for predicting the emission of pollutants in the work environment. Welding is one of the most common industrial processes that might expose the operators and surrounding workers to certain hazardous gaseous metal fumes. In the present study, we used computational fluid dynamics (CFD) methodology for simulating the emission of iron fumes from the shielded metal arc welding (SMAW) procedure. A galvanized steel chamber was fabricated to measure the pollutant concentration and identify the size of the fume created by the SMAW. Then, the emission of welding aerosol was simulated using a method of computational fluid-particle dynamics with the ANSYS 2020 R1 software. The highest amount of welding fumes concentration was related to iron fumes (i.e., 3045 μg/m³ with a diameter of 0.25 μm). The results of the current study indicated that the local exhaust and general ventilation system can prevent the spreading of welding fumes to the welder's breathing zone and the surrounding environment. CFD was also found to be an efficient method for predicting the emission of the iron fumes created by SMAW as well as for selecting an appropriate ventilation system. However, further studies that take the modeling of welding-generated emission of additional metal particles and gases into account will need to be undertaken.

A Numerical Simulation of the Airflow and Aerosol Particle Deposition in a Realistic Airway Model of a Healthy Adult

Determining the behavior of aerosol drug particles is of vital importance in the treatment of respiratory tract diseases. Despite the development of imaging techniques in the pulmonary region in recent years, current imaging techniques are insufficient to detect particle deposition. Computational fluid dynamics (CFD) methods can fill the gap in this field as they take into account the very different physical processes that occur during aerosol transport. This study aims to numerically investigate the airflow and the aerosol particle dynamics on a realistic human respiratory tract model during multiple breathing cycles. The simulations were conducted on the different breathing conditions for people under light, normal, and heavy physical activities, and the aerosol particles with different aerodynamic diameters (i.e., dp=2, 5, and 7 µm). The numerical results were validated by comparing extensively with experimental and numerical results. The results indicated that the airflow during inspiration and expiration was characteristically different from each other and changed with the inspiration flow rate. It was determined that small-sized particles followed the streamlines and moved towards the distal of the lung under low respiratory conditions. On the other hand, larger particles tended to deposit in higher generations due to the higher inertia. It was found that with the increase of inspiration flow rate the deposition of particles increased for all particles during multiple breaths. For light breathing conditions, low deposition efficiencies were obtained because the particles followed the streamlines and moved towards the distal part of the lung. The particle deposition efficiency under heavy breathing conditions was 28.2% for 2 µm, 33.05% for 5 µm, and 38.4% for 7 µm particles. The results showed that inertial impaction plays an active role in particle deposition.

Towards understanding respiratory particle transport and deposition in the human respiratory system: Effects of physiological conditions and particle properties

Fly ash is a common solid residue of incineration plants and poses a great environmental concern because of its toxicity upon inhalation exposure. The inhalation health impacts of fly ash is closely related to its transport and deposition in the human respiratory system which warrants significant research for health guideline setting and inhalation exposure protection. In this study, a series of fly ash transport and deposition experiments have been carried out in a bifurcation airway model by optical aerosol sampling analysis. Three types of fly ash samples of different morphologies were tested and their respiratory deposition and transport processes were compared. The deposition efficiencies were calculated and relevant transport dynamics mechanisms were discussed. The influences of physiological conditions such as breathing rate, duration, and fly ash physical properties (size, morphology, and specific surface area) were investigated. The deposition characteristics of respiratory particles containing SARS-CoV-2 has also been analyzed, which could further provide some guidance on COVID-19 prevention. The results could potentially serve as a basis for setting health guidelines and recommending personal respiratory protective equipment for fly ash handlers and people who are in the high exposure risk environment for COVID-19 transmission.

Recent developments in the computational simulation of dry powder inhalers

This article reviews recent developments in computational modeling of dry powder inhalers (DPIs). DPIs deliver drug formulations (sometimes blended with larger carrier particles) to a patient's lungs via inhalation. Inhaler design is complicated by the need for maximum aerosolization efficiency, which is favored by high levels of turbulence near the mouthpiece, with low extrathoracic depositional loss, which requires low turbulence levels near the mouth-throat region. In this article, we review the physical processes contributing to aerosolization and subsequent dispersion and deposition. We assess the performance characteristics of DPIs using existing simulation techniques and offer a perspective on how such simulations can be improved to capture the physical processes occurring over a wide range of length- and timescales more efficiently.

Analysis of improved oral drug delivery with different helical stream inhalation modes

A challenging aspect of pulmonary drug delivery devices, e.g., metered dose inhalers (MDIs), is to deliver therapeutic drugs to prescribed target locations at the required dosage level. In this study, validated computer simulations of micron-drug inhalation with angled or radially positioned helical fluid-particle streams are simulated and analyzed. For a suitable swirl number significant improvements in drug delivery, especially to deeper lung regions, have been achieved. Specifically, considering realistic polydisperse particle distributions at the mouth inlet for a subject-specific upper lung airway geometry, a 10-degree angled helical stream increased the local efficacy by up to 26% in comparison to a conventional helical stream, causing an overall dosage of about 60% to the deep lung. Considering lobe-specific drug targeting scenarios, while using an off-center, i.e., radially well positioned, helical-flow mouthpiece, the local particle-deposition efficacy increased from 9% to 24% in the left lobe and from 25% to 38% in the right lobe in comparison to conventional drug-aerosol stream released from the central position. The efficacy of helical streams for pulmonary drug delivery applications has been established.

LES study on the impact of airway deformation on the airflow structures in the idealized mouth–throat model

To investigate the impacts of upper airway deformation on the airflow structures, the airflow fields in the trachea are simulated using three geometrical models considering three different levels of airway deformations. Structured grids are used to create the high-quality grids. Large eddy simulation with the Smagorinsky sub-grid model is adopted to solve the three-dimensional in-compressible Navier–Stokes equations using the solver pisoFoam in the open-source CFD software OpenFOAM. The numerical results demonstrate that the airway deformation influences the main airflow structures depending on the deformation level. Particularly, it slightly impacts on the laryngeal jet such as the profile and the strength of laryngeal jet. The strength of the laryngeal jet increases slightly for the heavy deformation. In contrast, it impacts on the recirculation zone, secondary vortices, and turbulent kinetic energy more obviously. The increasing airway deformation will produce stronger secondary flow, smaller recirculation zone, and weaker turbulent kinetic energy. The turbulence intensity distribution varies as well. The obviously impacted flow region is mainly within the region of one to six tracheal diameters downstream the glottis.

Analysis of flow field and turbulence predictions in a lung model applying RANS and implications for particle deposition

Airflow and aerosol deposition in the human airways are important aspects for applications such as pulmonary drug delivery and human exposure to aerosol pollutants. Numerical simulations are widely used nowadays to shed light in airflow features and particle deposition patterns inside the airways. For that purpose, the Euler/Lagrange approach is adopted for predicting flow field and particle deposition through point-particle tracking. Steady-state RANS (Reynolds-averaged Navier-Stokes) computations of flow evolution in an extended lung model applying different turbulence models were conducted and compared to measurements as well as high resolution LES (large-eddy simulations) for several flow rates. In addition, various inlet boundary conditions were considered and their influence on the predicted flow field was analysed. The results showed that the mean velocity field was simulated reasonably well, however, turbulence intensity was completely under-predicted by two-equation turbulence models. Only a Reynolds-stress model (RSM) was able predicting a turbulence level comparable to the measurements and the high resolution LES. Remarkable reductions in wall deposition were observed when wall effects were accounted for in the drag and lift force expressions. Naturally, turbulence is an essential contribution to particle deposition and it is well known that two-equation turbulence models considerably over-predict deposition due to the spurious drift effect. A full correction of this error is only possible in connection with a Reynolds-stress turbulence model whereby the predicted deposition in dependence of particle diameter yielded better agreement to the LES predictions. Specifically, with the RSM larger deposition is predicted for smaller particles and lower deposition fraction for larger particles compared to LES. The local deposition fraction along the lung model was numerically predicted with the same trend as found from the measurements, however the values in the middle region of the lung model were found to be somewhat larger.

New Approach Methodology for Assessing Inhalation Risks of a Contact Respiratory Cytotoxicant: Computational Fluid Dynamics-Based Aerosol Dosimetry Modeling for Cross-Species and In Vitro Comparisons

Regulatory agencies are considering alternative approaches to assessing inhalation toxicity that utilizes in vitro studies with human cells and in silico modeling in lieu of additional animal studies. In support of this goal, computational fluid-particle dynamics models were developed to estimate site-specific deposition of inhaled aerosols containing the fungicide, chlorothalonil, in the rat and human for comparisons to prior rat inhalation studies and new human in vitro studies. Under bioassay conditions, the deposition was predicted to be greatest at the front of the rat nose followed by the anterior transitional epithelium and larynx corresponding to regions most sensitive to local contact irritation and cytotoxicity. For humans, simulations of aerosol deposition covering potential occupational or residential exposures (1-50 µm diameter) were conducted using nasal and oral breathing. Aerosols in the 1-5 µm range readily penetrated the deep region of the human lung following both oral and nasal breathing. Under actual use conditions (aerosol formulations >10 µm), the majority of deposited doses were in the upper conducting airways. Beyond the nose or mouth, the greatest deposition in the pharynx, larynx, trachea, and bronchi was predicted for aerosols in the 10-20 µm size range. Only small amounts of aerosols >20 µm penetrated past the pharyngeal region. Using the ICRP clearance model, local retained tissue dose metrics including maximal concentrations and areas under the curve were calculated for each airway region following repeated occupational exposures. These results are directly comparable with benchmark doses from in vitro toxicity studies in human cells leading to estimated human equivalent concentrations that reduce the reliance on animals for risk assessments.

Measurement of harmful nanoparticle distribution among filters, smokers' respiratory systems, and surrounding air during cigarette smoking

This study was undertaken to investigate the filtration effect of filter on nanoparticle and the deposition behavior of nanoparticle in the human respiratory system from the aspect of nanoparticle number during cigarette smoking. For that, two kinds of experiments were designed. One is machine experiment, a well-controlled simulated respiratory system was designed to measure the raw emission and filter effect. Another is human experiment, volunteers were asked to inhale smoke into the oral cavity only and lungs, respectively, to distinguish smoke path. Results revealed that effective inhaled nanoparticle amount of a Taishan and a Hongtaishan cigarette were 5.8E + 9 (#) and 9.4E + 7 (#), respectively. The filter's integrated reduction rate was 41.65% for nanoparticle. For Taishan cigarette, 35.4% and 41.7% of raw emitted nanoparticles were deposited in the oral cavity and lungs, respectively, the rest of 22.9% was exhaled to surrounding air. The corresponding values were 25.6%, 41.5% and 32.9%, respectively, for Hongtaishan. The current findings are expected to provide basic assessments of filter effect and harm to human and to be a warning for smokers.

A quasi-3D model of the whole lung: airway extension to the tracheobronchial limit using the constrained constructive optimization and alveolar modeling, using a sac-trumpet model

Existing computational models used for simulating the flow and species transport in the human airways are zero-dimensional (0D) compartmental, three-dimensional (3D) computational fluid dynamics (CFD), or the recently developed quasi-3D (Q3D) models. Unlike compartmental models, the full CFD and Q3D models are physiologically and anatomically consistent in the mouth and the upper airways, since the starting point of these models is the mouth-lung surface geometry, typically created from computed tomography (CT) scans. However, the current resolution of CT scans limits the airway detection between the 3rd-4th and 7th-9th generations. Consequently, CFD and the Q3D models developed using these scans are generally limited to these generations. In this study, we developed a method to extend the conducting airways from the end of the truncated Q3D lung to the tracheobronchial (TB) limit. We grew the lung generations within the closed lung lobes using the modified constrained constructive optimization, creating an aerodynamically optimized network aiming to produce equal pressure at the distal ends of the terminal segments. This resulted in a TB volume and lateral area of ∼165 cc and ∼2000 cm², respectively. We created a "sac-trumpet" model at each of the TB outlets to represent the alveoli. The volumes of the airways and the individual alveolar generations match the anatomical values by design: with the functional residual capacity at 2611 cc. Lateral surface areas were scaled to match the physiological values. These generated Q3D whole lung models can be efficiently used for conducting multiple breathing cycles of drug transport and deposition simulations.

Role of CFD based in silico modelling in establishing an in vitro-in vivo correlation of aerosol deposition in the respiratory tract

Effective evaluation and prediction of aerosol transport deposition in the human respiratory tracts are critical to aerosol drug delivery and evaluation of inhalation products. Establishment of an in vitro-in vivo correlation (IVIVC) requires the understanding of flow and aerosol behaviour and underlying mechanisms at the microscopic scale. The achievement of the aim can be facilitated via computational fluid dynamics (CFD) based in silico modelling which treats the aerosol delivery as a two-phase flow. CFD modelling research, in particular coupling with discrete phase model (DPM) and discrete element method (DEM) approaches, has been rapidly developed in the past two decades. This paper reviews the recent development in this area. The paper covers the following aspects: geometric models of the respiratory tract, CFD turbulence models for gas phase and its coupling with DPM/DEM for aerosols, and CFD investigation of the effects of key factors associated with geometric variations, flow and powder characteristics. The review showed that in silico study based on CFD models can effectively evaluate and predict aerosol deposition pattern in human respiratory tracts. The review concludes with recommendations on future research to improve in silico prediction to achieve better IVIVC.

Numerical simulation of the unsteady flow field in the human pulmonary acinus

Understanding of airflow dynamics in the human pulmonary acinus is important for increasing targeted drug effectiveness and determining the health impact of toxic aerosols. However, there is a lack of quantitative data about the pulmonary airflow in realistic and flexible idealized geometries. This paper aims to numerically analyse the flow field of the pulmonary acinus using the computational fluid dynamics (CFD) model during transient breathing. Three-dimensional models with rhythmically expanding-contracting alveolar walls were developed for representing the pulmonary region of the human lung. Three different breathing scenarios were applied in the CFD simulations. The results showed that the transient flow conditions determined the transitions between flow types. The recirculating flow in the alveoli was observed for all cases and it was determined that its intensity depended on the breathing scenario. The flow velocity in the alveoli was slower than that of the channel flow. As we moved deeper into the lung, the flow pattern inside the alveoli exhibited a radial velocity profile. It was found that the alveolar flow exhibited a typical stenotic channel flow characteristics. As a result, the acinus models used in this study takes into account the alveolar wall motion based on physiological breathing conditions. To simulate or estimate the airflow dynamics, thus, the results obtained in this study can be easily utilized in the human lung airway models.

Efficient bi-directional coupling of 3D Computational Fluid-Particle Dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. As a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 μm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFPD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. These methods can be used as the foundation for multi-scale modeling of the full respiratory system.

A numerical study of the aerosol behavior in intra-acinar region of a human lung

The determination of the particle dynamics in the human acinar airways having millions of alveoli is critical in preventing potential health problems and delivering therapeutic particles effectively to target locations. Despite its complex geometrical structure and complicate wall movements, the advanced calculation simulations can provide valuable results to accurately predict the aerosol deposition in this region. The objective of this study was to numerically investigate the aerosol particle transport and deposition in the intra-acinar region of a human lung for different breathing scenarios (i.e., light, normal, and heavy activities) during multiple breaths. Idealized intra-acinar models utilized in this study consisted of a respiratory bronchial model, an alveolar duct model, and an alveolar sac model. The particles with 5 μm in diameter released from the inlet of the model were tracked until they deposited or escaped from the computational domain. The results showed that due to the rhythmic alveolar wall movement, the flow field was divided into two regions: one is the low-speed alveolar flow and the other is the channel flow. It was found that the chaotic acinar flow irreversibility played a significant role in the aerosol transport in higher generations. During the succeeding breaths, more particles deposited or escaped to the relating acinar generation and reached the more distal regions of the lung. The number of particles remaining in the suspension at the end of the third cycle ranged from 0.016% to 3%. When the mouth flow rate increased, the number of particles remaining in the suspension reduced, resulting in higher deposition efficiency. The total deposition efficiencies for each flow rate were 24%, 47%, and 77%, respectively. The particle simulation results also showed that more breathing cycle was required for full aerosol particle deposition or escape from the model. In addition to the alveolar wall motion, the type of breathing condition and breathing cycle had a significant effect on the accurate prediction of the aerosol deposition in the intra-acinar region of the human lung.

AVATREE: An open-source computational modelling framework modelling Anatomically Valid Airway TREE conformations

This paper presents AVATREE, a computational modelling framework that generates Anatomically Valid Airway tree conformations and provides capabilities for simulation of broncho-constriction apparent in obstructive pulmonary conditions. Such conformations are obtained from the personalized 3D geometry generated from computed tomography (CT) data through image segmentation. The patient-specific representation of the bronchial tree structure is extended beyond the visible airway generation depth using a knowledge-based technique built from morphometric studies. Additional functionalities of AVATREE include visualization of spatial probability maps for the airway generations projected on the CT imaging data, and visualization of the airway tree based on local structure properties. Furthermore, the proposed toolbox supports the simulation of broncho-constriction apparent in pulmonary diseases, such as chronic obstructive pulmonary disease (COPD) and asthma. AVATREE is provided as an open-source toolbox in C++ and is supported by a graphical user interface integrating the modelling functionalities. It can be exploited in studies of gas flow, gas mixing, ventilation patterns and particle deposition in the pulmonary system, with the aim to improve clinical decision making.

Particle transport and deposition correlation with near-wall flow characteristic under inspiratory airflow in lung airways

Exposure of lung airways to detrimental suspended aerosols in the environment increases the vulnerability of the respiratory and cardiovascular systems. In addition, recent developments in therapeutic inhalation devices magnify the importance of particle transport. In this manuscript, particle transport and deposition patterns in the upper tracheobronchial (TB) tree were studied where the inertial forces are considerable for microparticles. Wall shear stress divergence (WSSdiv) is proposed as a wall-based parameter that can predict particle deposition patterns. WSSdiv is proportional to near-wall normal velocity and can quantify the strength of flow towards and away from the wall. Computational fluid dynamics (CFD) simulations were performed to quantify airflow velocity and WSS vectors for steady inhalation in one case-control and unsteady inhalation in six subject-specific airway trees. Turbulent flow simulation was performed for the steady case using large eddy simulation to study the effect of turbulence. Magnetic resonance velocimetry (MRV) measurements were used to validate the case-control CFD simulation. Inertial particle transport was modeled by solving the Maxey-Riley equation in a Lagrangian framework. Deposition percentage (DP) was quantified for the case-control model over five particle sizes. DP was found to be proportional to particle size in agreement with previous studies in the literature. A normalized deposition concentration (DC) was defined to characterize localized deposition. A relatively strong correlation (Pearson value > 0.7) was found between DC and positive WSSdiv for physiologically relevant Stokes (St) numbers. Additionally, a regional analysis was performed after dividing the lungs into smaller areas. A spatial integral of positive WSSdiv over each division was shown to maintain a very strong correlation (Pearson value > 0.9) with cumulative spatial DC or regional dosimetry. The conclusions were generalized to a larger population in which two healthy and four asthmatic patients were investigated. This study shows that WSSdiv could be used to predict the qualitative surface deposition and relative regional dosimetry without the need to solve a particle transport problem.

Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates

The measurement of deposited aerosol particles in the respiratory tract via in vivo and in vitro approaches is difficult due to those approaches’ many limitations. In order to overcome these obstacles, different computational models have been developed to predict the deposition of aerosol particles inside the lung. Recently, some remarkable models have been developed based on conventional semi-empirical models, one-dimensional whole-lung models, three-dimensional computational fluid dynamics models, and artificial neural networks for the prediction of aerosol-particle deposition with a high accuracy relative to experimental data. However, these models still have some disadvantages that should be overcome shortly. In this paper, we take a closer look at the current research trends as well as the future directions of this research area.

Regional flow and deposition variability in adult female lungs: A numerical simulation pilot study

BACKGROUND

Despite the promise of respiratory simulations improving diagnosis and treatment of pulmonary diseases, model predictions have yet to be translated into the clinical setting. Current state-of-the-art in silico models have not yet incorporated subject variability in their predictions of airflow distributions and extent of deposited particles. Until inter-subject variability is accounted for in lung modeling, it will remain impossible to translate model predictions into clinical practice.

METHODS

Airflow and particle trajectories (d_p=1,3,5μm) are calculated in three subject-specific female adults by performing physiologically-based simulations. The computation framework features the ability to track air and particles throughout the respiration cycle and in the entire lung. Airway resistances, air velocities, and local deposition sites are correlated to airway anatomical features.

FINDINGS

Smaller airway diameters are correlated to larger airway resistances and pressure gradients in one subject compared to the other two. Irregular shape of the airway and flow direction (e.g. inspiration or expiration) correspond with peak velocities and secondary flow motions. Largest subject variability in deposition between conducting and respiratory zones is seen for 1 μm diameter particles. Little difference in total deposition is found among subjects. Localized deposited particle concentration hotspots are linked to airway anatomy and flow motion.

INTERPRETATION

Simulation predictions provide a first look into the correlation of anatomical features with airflow characteristics and deposited particle concentrations. Global deposition percentages ranged (at most, by 20%) between subjects and variances in localized deposition hotspots are correlated to variances in flow characteristics.

Modeling Airflow and Particle Deposition in a Human Acinar Region

The alveolar region, encompassing millions of alveoli, is the most vital part of the lung. However, airflow behavior and particle deposition in that region are not fully understood because of the complex geometrical structure and intricate wall movement. Although recent investigations using 3D computer simulations have provided some valuable information, a realistic analysis of the air-particle dynamics in the acinar region is still lacking. So, to gain better physical insight, a physiologically inspired whole acinar model has been developed. Specifically, air sacs (i.e., alveoli) were attached as partial spheroids to the bifurcating airway ducts, while breathing-related wall deformation was included to simulate actual alveolar expansion and contraction. Current model predictions confirm previous notions that the location of the alveoli greatly influences the alveolar flow pattern, with recirculating flow dominant in the proximal lung region. In the midalveolar lung generations, the intensity of the recirculating flow inside alveoli decreases while radial flow increases. In the distal alveolar region, the flow pattern is completely radial. The micron/submicron particle simulation results, employing the Euler–Lagrange modeling approach, indicate that deposition depends on the inhalation conditions and particle size. Specifically, the particle deposition rate in the alveolar region increases with higher inhalation tidal volume and particle diameter. Compared to previous acinar models, the present system takes into account the entire acinar region, including both partially alveolated respiratory bronchioles as well the fully alveolated distal airways and alveolar sacs. In addition, the alveolar expansion and contraction have been calculated based on physiological breathing conditions which make it easy to compare and validate model results with in vivo lung deposition measurements. Thus, the current work can be readily incorporated into human whole-lung airway models to simulate/predict the flow dynamics of toxic or therapeutic aerosols.

Particle deposition in the human lung: Health implications of particulate matter from different sources

Although ambient particulate matter or particles have been found to be associated with morbidity and mortality all over the world, specific health effects of particles from different sources need further elucidation. The objective of this work is to predict the deposition of particles from different sources in the human lung. The whole lung, consisting of 24 generations of branches from trachea to alveoli, was approximated using a one-dimensional lumped "trumpet" model with a variable cross-sectional area. The aerosol dynamics equation was numerically solved using a finite difference method to investigate the transport and deposition of particles in the lung model. Particles from various sources were assumed to be different in both size and density. We found that in general, coarse particles (> 2.5 µm) were mainly deposited in the tracheobronchial (TB) region by impaction, and fine particles (< 2.5 µm) were mainly deposited in the pulmonary (P) region by sedimentation and diffusion. However, the coarse particles with low density can be deposited in P region by sedimentation. As a comparison, our results found that soil particles, which are coarse with low density, were deposited in the deep lung more than traffic particles, which are fine with high density. Modeling of particle deposition in the human lung indicated that coarse particles generated by crustal sources may have adverse health effects as strong as those resulting from fine particles generated from combustion sources.

Use of computational fluid dynamics deposition modeling in respiratory drug delivery

INTRODUCTION

Respiratory drug delivery is a surprisingly complex process with a number of physical and biological challenges. Computational fluid dynamics (CFD) is a scientific simulation technique that is capable of providing spatially and temporally resolved predictions of many aspects related to respiratory drug delivery from initial aerosol formation through respiratory cellular drug absorption.

AREAS COVERED

This review article focuses on CFD-based deposition modeling applied to pharmaceutical aerosols. Areas covered include the development of new complete-airway CFD deposition models and the application of these models to develop a next-generation of respiratory drug delivery strategies.

EXPERT OPINION

Complete-airway deposition modeling is a valuable research tool that can improve our understanding of pharmaceutical aerosol delivery and is already supporting medical hypotheses, such as the expected under-treatment of the small airways in asthma. These complete-airway models are also being used to advance next-generation aerosol delivery strategies, like controlled condensational growth. We envision future applications of CFD deposition modeling to reduce the need for human subject testing in developing new devices and formulations, to help establish bioequivalence for the accelerated approval of generic inhalers, and to provide valuable new insights related to drug dissolution and clearance leading to microdosimetry maps of drug absorption.

Mice-to-men comparison of inhaled drug-aerosol deposition and clearance

Part of the effective prediction of the pharmacokinetics of drugs (or toxic particles) requires extrapolation of experimental data sets from animal studies to humans. As the respiratory tracts of rodents and humans are anatomically very different, there is a need to study airflow and drug-aerosol deposition patterns in lung airways of these laboratory animals and compare them to those of human lungs. As a first step, interspecies computational comparison modeling of inhaled nano-to-micron size drugs (50 nm < d<15μm) was performed using mouse and human upper airway models under realistic breathing conditions. Critical species-specific differences in lung physiology of the upper airways and subsequently in local drug deposition were simulated and analyzed. In addition, a hybrid modeling methodology, combining Computational Fluid-Particle Dynamics (CF-PD) simulations with deterministic lung deposition models, was developed and predicted total and regional drug-aerosol depositions in lung airways of both mouse and man were compared, accounting for the geometric, kinematic and dynamic differences. Interestingly, our results indicate that the total particle deposition fractions, especially for submicron particles, are comparable in rodent and human respiratory models for corresponding breathing conditions. However, care must be taken when extrapolating a given dosage as considerable differences were noted in the regional particle deposition pattern. Combined with the deposition model, the particle retention and clearance kinetics of deposited nanoparticles indicates that the clearance rate from the mouse lung is higher than that in the human lung. In summary, the presented computer simulation models provide detailed fluid-particle dynamics results for upper lung airways of representative human and mouse models with a comparative analysis of particle lung deposition data, including a novel mice-to-men correlation as well as a particle-clearance analysis both useful for pharmacokinetic and toxicokinetic studies.

Application of a One-Dimensional Computational Model for the Prediction of Deposition from a Dry Powder Inhaler

BACKGROUND

Accurate prediction of the regional deposition of inhaled dry powders as a function of powder properties and breathing pattern is a long-term research goal for pulmonary drug delivery. In the present work, deposition along the respiratory tract of dry powders of Fluticasone propionate and Salmeterol is predicted.

METHODS

A one-dimensional particle transport and deposition model is used, whose novelty is in the treatment of the alveolar space of each airway generation as an efficient mixing chamber. This assumption has been supported by simulations and measurements during the last 20 years. The model is applied to two popular pulmonary tree geometries, to investigate the effect of particle size on localized deposition and to estimate the uncertainty due to variations in airway size.

RESULTS AND CONCLUSIONS

Application of the model for the specific particle size distribution measured by a cascade impactor in the marketed product ELPENhaler, predicts the whole lung deposition (WLD), as well as the split between pulmonary (PU) and tracheobronchial (TB) deposition. Introduction in the model of modified particle size distributions with increased fractions of fine particles, indicates that the fine-particle dose is a satisfactory predictor of WLD but not of the PU/TB ratio.