Pharmaceutical aerosols deposition patterns from a Dry Powder Inhaler: Euler Lagrangian prediction and validation

Numerical modeling of particle deposition in a realistic respiratory airway using CFD-DPM and genetic algorithm

In this study, a realistic model of the respiratory tract obtained from CT medical images was used to solve the flow field and particle motion using the Eulerian-Lagrangian approach to obtain the maximum particle deposition in the bronchial tree for the main purpose of optimizing the performance of drug delivery devices. The effects of different parameters, including particle diameter, particle shape factor, and air velocity, on the airflow field and particle deposition pattern in different zones of the lung were investigated. In addition, a genetic algorithm was employed to obtain the maximum particle deposition in the bronchial tree and the effect of the aforementioned parameters on particle deposition. Reverse flow, vortex formation, and laryngeal jet all affect the airflow structure and particle deposition pattern. The mouth-throat region had the highest deposition fraction at various flow rates. A change in the deposition pattern with an increased deposition fraction in the throat was observed owing to the increased diameter and shape factor of the particles, resulting from the higher inertia and drag force, respectively. The particle deposition analysis showed that three parameters, shape factor, diameter, and velocity, are directly related to particle deposition, and the diameter is the most effective parameter for particle deposition, with an effect of 60% compared to the shape factor and velocity. Finally, the prediction of the genetic algorithm reported a maximum particle deposition in the bronchial tree of 17%, whereas, based on the numerical results, the maximum particle deposition was reported to be 16%. Therefore, there is a 1% difference between the prediction of the genetic algorithm and the numerical results, which indicates the high accuracy of the prediction of the genetic algorithm.

Validation of computational fluid dynamics models for airway deposition with SPECT data of the same population

This study compared computational fluid dynamic (CFD) model predictions on aerosol deposition in six asthmatic patients to the in-vivo results of the same group. Patient-specific ventilation and internal air distribution were prescribed using inspiratory and expiratory CT scans of each patient, accounting for individual lobar air flow distribution. Moreover, the significant influence of realistic mouth and throat geometries on regional deposition is demonstrated. The in-vivo data were obtained from single photon emission computed tomography (SPECT) in 6 subjects with mild asthma selected from a database of historical clinical trials. The governing flow and particle tracking equations were solved numerically using a commercial CFD tool, and the modeled deposition results were compared to the SPECT data. Good agreement was found between the CFD model, applying k-ω SST turbulence model, and SPECT in terms of aerosol deposition. The average difference for the lobar deposition obtained from CFD model and SPECT/CT data was 2.1%. The high level of agreement is due to applying patient specific airway geometries and inspiratory/expiratory CT images, anatomical upper airways, and realistic airway trees. The results of this study show that CFD is a powerful tool to simulate patient-specific deposition if correct boundary conditions are applied and can generate similar information obtained with functional imaging tools, such as SPECT.

Effect of laryngeal jet on dry powder inhaler aerosol deposition: a numerical simulation

Although pulmonary drug delivery has been deeply investigated, the effect of the laryngeal jet on particle deposition during drug delivery with dry powder inhalers (DPI) has not been evaluated profoundly. In this study, the flow structure and particle deposition pattern of a DPI in two airway models, one with mouth-throat region including the larynx and the other one without it, are numerically investigated. The results revealed that the laryngeal jet has a considerable effect on particle deposition. The presence of laryngeal jet leads to 4-fold and 2-fold higher deposition efficiencies for inlet flow rates of 30 and 90 L/min, respectively.

The impact of endotracheal intubation on oxygen delivery, trachea pressure and wall deformation

This paper concerns improving endotracheal tube (ETT) insertion through advanced computational science modelling. The study aims to better understand endotracheal intubation (ETI) and reduce medical errors in intensive and critical care units since ETT insertion is unique for each patient, depending on age, gender, size, physiology, and underlying health conditions. We have employed computational fluid dynamics and biomechanics modelling to investigate the effect of ETT for three ventilation modes on (a) local oxygen delivery to the lungs, (b) air pressure and wall shear stress at the tracheal walls, and (c) oscillatory elastic deformation of the tracheal tissues and muscle. For the first time, we reveal how the ventilation mode and ETT insertion in the trachea may induce major complications, especially in long periods of ETT. We show that rotating the ETT or displacing it by 2 mm only can induce a significant rise in the tracheal pressure up to 177 cmH2O. This study, for the first time, shows the vital role of computers in biology and medicine to provide enhanced decision-making-support to clinicians and medical doctors dealing with ETI.

Predicting particle deposition using a simplified 8-path in silico human lung prototype

Understanding particle deposition in the human lung is crucial for the assessment of environmental pollutants and the design of new drug delivery systems. Traditionally, research has been carried out by experimental analysis, but this generally requires expensive equipment and exposure of volunteers to radiation, resulting in limited data. To overcome these drawbacks, there is an emphasis on the development of numerical models capable of accurate predictive analysis. The most advanced of these computer simulations are based on three-dimensional computational fluid dynamics. Solving the flow equations in a complete, fully resolved lung airway model is currently not feasible due to the computational resources required. In the present work, a simplified lung model is presented and validated for accurate prediction of particle deposition. Simulations are performed for an 8-path approximation to a full lung airway model. A novel boundary condition method is used to ensure accurate results in truncated flow branches. Simulations are performed at a steady inhalation flow rate of 18 l min-1, corresponding to a low activity breathing rate, while the effects of particle size and density are investigated. Comparison of the simulation results with available experimental data shows that reasonably accurate results can be obtained at a small fraction of the cost of a full airway model. The simulations clearly evaluate the effect of both particle size and particle density. Most importantly, the results show an improvement over a previously documented single-path model, both in terms of accuracy and the ability to obtain regional deposition rates. The present model represents an improvement over previously used simplified models, including single-path models. The multi-path reduced airway approach described can be used by researchers for general and patient-specific analyses of particle deposition and for the design of effective drug delivery systems.

Scientific and regulatory activities initiated by the U.S. Food and drug administration to foster approvals of generic dry powder inhalers: Bioequivalence perspective

Regulatory science for generic dry powder inhalers (DPIs) in the United States (U.S.) has evolved over the last decade. In 2013, the U.S. Food and Drug Administration (FDA) published the draft product-specific guidance (PSG) for fluticasone propionate and salmeterol xinafoate inhalation powder. This was the first PSG for a DPI available in the U.S., which provided details on a weight-of-evidence approach for establishing bioequivalence (BE). A variety of research activities including in vivo and in vitro studies were used to support these recommendations, which have led to the first approval of a generic DPI in the U.S. for fluticasone propionate and salmeterol xinafoate inhalation powder in January of 2019. This review describes the scientific and regulatory activities that have been initiated by FDA to support the current BE recommendations for DPIs that led to the first generic DPI approvals, as well as research with novel in vitro and in silico methods that may potentially facilitate generic DPI development and approval.

Count- and mass-based dosimetry of MDI spray droplets with polydisperse and monodisperse size distributions

Most previous numerical studies of inhalation drug delivery used monodisperse aerosols or quantified deposition as the ratio of deposited particle number over the total number of released particles (i.e., count-based). These practices are reasonable when the aerosols have a sufficiently narrow size range. However, spray droplets from metered-dose inhalers (MDIs) are often polydisperse with a wide size range, so using monodisperse aerosols and/or count-based deposition quantification may lead to significant errors. The objective of this study was to develop a mass-based dosimetry method and evaluate its performance in lung delivery in a mouth-lung (G9) geometry with an albuterol-CFC inhaler. The conventional practices (monodisperse and polydisperse-count-based) were also simulated for comparison purposes. The MDI actuation in the open space was studied using both high-speed imaging and LES-Lagrangian simulations. Experimentally measured spray velocities and size distribution were implemented in the computational model as boundary conditions. Good agreement was achieved between recorded and simulated spray plume evolution spatially and temporally. The polydisperse-mass-based predictions of MDI doses compared favorably with the measurements in all three regions considered (device, mouth-throat, and lung). Significant errors in MDI regional deposition were predicted using the monodisperse and count-based methods. The new polydisperse-mass-based method also predicted local deposition hot spots that were one order of magnitude higher in intensity than the two conventional methods. The results of this study highlighted that a presentative polydisperse size distribution and appropriate deposition quantification method should be applied to reliably predict the MDI drug delivery in the human respiratory tract.

Experimental Evaluation of Dry Powder Inhalers during Inhalation and Exhalation Using a Model of the Human Respiratory System (xPULM™)

Dry powder inhalers are used by a large number of patients worldwide to treat respiratory diseases. The objective of this work is to experimentally investigate changes in aerosol particle diameter and particle number concentration of pharmaceutical aerosols generated by four dry powder inhalers under realistic inhalation and exhalation conditions. To simulate patients undergoing inhalation therapy, the active respiratory system model (xPULM™) was used. A mechanical upper airway model was developed, manufactured, and introduced as a part of the xPULM™ to represent the human upper respiratory tract with high fidelity. Integration of optical aerosol spectrometry technique into the setup allowed for evaluation of pharmaceutical aerosols. The results show that there is a significant difference (p < 0.05) in mean particle diameter between inhaled and exhaled particles with the majority of the particles depositing in the lung, while particles with the size of (>0.5 μm) are least influenced by deposition mechanisms. The fraction of exhaled particles ranges from 2.13% (HandiHaler®) over 2.94% (BreezHaler®), and 6.22% (Turbohaler®) to 10.24% (Ellipta®). These values are comparable to previously published studies. Furthermore, the mechanical upper airway model increases the resistance of the overall system and acts as a filter for larger particles (>3 μm). In conclusion, the xPULM™ active respiratory system model is a viable option for studying interactions of pharmaceutical aerosols and the respiratory tract regarding applicable deposition mechanisms. The model strives to support the reduction of animal experimentation in aerosol research and provides an alternative to experiments with human subjects.

Combining experimental and computational techniques to understand and improve dry powder inhalers

INTRODUCTION

: Dry Powder Inhalers (DPIs) continue to be developed to deliver an expanding range of drugs to treat an ever-increasing range of medical conditions; with each drug and device combination needing a specifically designed inhaler. Fast regulatory approval is essential to be first to market, ensuring commercial profitability.

AREAS COVERED

: In vitro deposition, particle image velocimetry, and computational modelling using the physiological geometry and representative anatomy can be combined to give complementary information to determine the suitability of a proposed inhaler design and to optimise its formulation performance. In combination they allow the entire range of questions to be addressed cost-effectively and rapidly.

EXPERT OPINION

: Experimental techniques and computational methods are improving rapidly, but each needs a skilled user to maximize results obtained from these techniques. Multidisciplinary teams are therefore key to making optimal use of these methods and such qualified teams can provide enormous benefits to pharmaceutical companies to improve device efficacy and thus time to market. There is already a move to integrate the benefits of Industry 4.0 into inhaler design and usage, a trend that will accelerate.

Computational pharmaceutics - A new paradigm of drug delivery

In recent decades pharmaceutics and drug delivery have become increasingly critical in the pharmaceutical industry due to longer time, higher cost, and less productivity of new molecular entities (NMEs). However, current formulation development still relies on traditional trial-and-error experiments, which are time-consuming, costly, and unpredictable. With the exponential growth of computing capability and algorithms, in recent ten years, a new discipline named "computational pharmaceutics" integrates with big data, artificial intelligence, and multi-scale modeling techniques into pharmaceutics, which offered great potential to shift the paradigm of drug delivery. Computational pharmaceutics can provide multi-scale lenses to pharmaceutical scientists, revealing physical, chemical, mathematical, and data-driven details ranging across pre-formulation studies, formulation screening, in vivo prediction in the human body, and precision medicine in the clinic. The present paper provides a comprehensive and detailed review in all areas of computational pharmaceutics and "Pharma 4.0", including artificial intelligence and machine learning algorithms, molecular modeling, mathematical modeling, process simulation, and physiologically based pharmacokinetic (PBPK) modeling. We not only summarized the theories and progress of these technologies but also discussed the regulatory requirements, current challenges, and future perspectives in the area, such as talent training and a culture change in the future pharmaceutical industry.

Effect of swirling flow and particle-release pattern on drug delivery to human tracheobronchial airways

The present study aims to investigate the effect of swirling flow on particle deposition in a realistic human airway. A computational fluid dynamic (CFD) model was utilized for the simulation of oral inhalation and particle transport patterns, considering the k-ω turbulence model. Lagrangian particle tracking was used to track the particles' trajectories. A normal breathing condition (30 L/min) was applied, and two-micron particles were injected into the mouth, considering swirling flow to the oral inhalation airflow. Different cases were considered for releasing the particles, which evaluated the impacts of various parameters on the deposition efficiency (DE), including the swirl intensity, injection location and pattern of the particle. The work's novelty is applying several injection locations and diameters simultaneously. The results show that the swirling flow enhances the particle deposition efficiency (20-40%) versus no-swirl flow, especially in the mouth. However, releasing particles inside the mouth, or injecting them randomly with a smaller injection diameter (d_inj) reduced DE in swirling flow condition, about 50 to 80%. Injecting particles inside the mouth can decrease DE by about 20%, and releasing particles with smaller d_inj leads to 50% less DE in swirling flow. In conclusion, it is indicated that the airflow condition is an important parameter for a reliable drug delivery, and it is more beneficial to keep the inflow uniform and avoid swirling flow.

Particle-based coarse-grained approach for simulating dry powder inhaler

Drug delivery via dry powder inhaler (DPI) is a complex process affected by multiple factors involving gas and particles. The performance of a carrier-based formulation depends on the release of active pharmaceutical ingredient (API) particles, typically characterized by fine particle fraction (FPF) and dispersion fraction (DF). Computational Fluid Dynamics coupled with Discrete Element Method (CFD-DEM) can capture relevant gas and particle interactions but is computationally expensive, especially when tracking all carrier and API particles. This study assessed the efficacy of two coarse-grained CFD-DEM approaches, the Discrete Parcel Method and the representative particle approach, through highly-resolved CFD-DEM simulations. The representative particle approach simulates all carrier particles and a subset of API particles, whereas the Discrete Parcel Method tracks parcels representing a specified number of carrier or API particles. Both approaches are viable for a small carrier-API size ratio which requires modest degrees of coarse-graining, but the Discrete Parcel Method showed limitations for a large carrier-API size ratio. The representative particle approach can approximate CFD-DEM results with reasonable accuracies when simulations include at least 10 representative API particles per carrier. Using the representative particle approach, we probed powder characteristics that could affect FPF and DF in a model problem and correlated these fractions with the maximum carrier-API cohesive force per unit mass of API particles.

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.

A multiscale absorption and transit model for oral delivery of hydroxychloroquine: Pharmacokinetic modeling and intestinal concentration prediction to assess toxicity and drug-induced damage in healthy subjects

Hydroxychloroquine (HCQ) is commonly used in the treatment of malaria and rheumatic diseases. Recently it has also been identified as possible therapeutic option in combating COVID-19. However, the use of HCQ is known to induce cytotoxicity. In 2020, we developed a multiscale absorption and transit (MAT) toolkit to simulate the dissolution, transport, absorption, distribution, metabolism, and elimination of orally administered drugs in the human GIT at multiple levels. MAT was constructed by integrating the spatially accurate first-principles driven high-fidelity drug transport, dissolution, and absorption model in the human stomach and GIT using the recently published Quasi-3D framework. The computational results showed that MAT was able to match the experimental concentration results better than the traditional compartmental models. In this study, we adapted MAT, to predict the pharmacokinetics of orally delivered HCQ in healthy subjects. The computational results matched the experimental concentration results. The simulated stomach and intestinal fluid and enterocyte concentrations were compared with the in vitro CC50 values. While the peak enterocyte concentrations were several orders lower than the in vitro CC50 values, the peak stomach and the intestinal fluid concentrations were only one order smaller than the in vitro CC50 values. In particular, the peak stomach and the duodenum fluid concentrations were just 3× smaller than the in vitro CC50 values. This implies that the lumen walls are much more susceptible to cytotoxicity-based damage than the enterocyte layers. We envision that MAT can be used to optimize the dosing regimen of HCQ by maximizing its bioavailability, while simultaneously minimizing the cytotoxic damage.

In silico prototype of a human lung with a single airway to predict particle deposition

BACKGROUND

Experimental analyses of the flow of drug particles inside the human lung usually require that the patient be exposed to radiation and also of expensive equipment that often lack of enough accuracy. Numerical calculations based on CFD (computational fluid dynamics) have been proven to be a valuable tool to analyze flows in diverse applications.

METHODS

The complexity of the human lung disallows running calculations on complete lung models due to the large number of cells that would be required. In this work, using a proprietary methodology, particle deposition in the lung is simulated by reducing its multiple branches to a single path.

RESULTS

The tested flow rates were 18, 30, and 75 L min^-1 , which are equivalent to different respiratory rates varying from light activity to heavy exercise. Most of the particles are accumulated in the upper airways, mainly at the mouth and also at the confluence of the larynx and the trachea (epiglottis), while the remaining particles travel across the lung. The reported procedure allowed simulating the operation of the entire lung by means of a single individual path.

CONCLUSIONS

The obtained calculations are in good agreement with the experimental results found in the technical literature, thus showing that the model can provide a realistic description of the lung operation, while avoiding high computational costs. Moreover, the calculations suggest that particle sizes above 15 μm and inspiratory flows higher than 30 L min^-1 must be avoided in order to allow drug particles to reach the lower airways.

Anthropometry-based generation of personalized and population-specific human airway models

Understanding aerosol deposition in the human lung is of great significance in pulmonary toxicology and inhalation pharmacology. Adverse effects of inhaled environmental aerosols and pharmacological efficacy of inhaled therapeutics are dependent on aerosol properties as well as person-specific respiratory tract anatomy and physiology. Anatomical geometry and physiological function of human airways depend on age, gender, weight, fitness, health, and disease status. Tools for the generation of the population- and subject-specific virtual airway anatomical geometry based on anthropometric data and physiological vitals are invaluable in respiratory diagnostics, personalized pulmonary pharmacology, and model-based management of chronic respiratory diseases. Here we present a novel protocol and software framework for the generation of subject-specific airways based on anthropometric measurements of the subject's body, using the anatomical input, and the conventional spirometry, providing the functional (physiological) data. This model can be used for subject-specific simulations of respiration physiology, gas exchange, and aerosol inhalation and deposition.

A multiscale absorption and transit model for oral drug delivery: Formulation and applications during fasting conditions

Most Food and Drug Administration (FDA)-approved drugs are administered orally, despite the complex process of oral drug absorption that is difficult to analyze experimentally. Oral bioavailability is dependent on the drug compound as well as the physiological and anatomical states of the user. Thus, computational models have emerged to mechanistically capture and predict the oral absorption process. The current models are generally 0D compartmental models and are limited by (a) simplified physiological characteristics of the gastrointestinal tract (GIT), (b) semiempirical/analytical dissolution profiles of the tested drugs, (c) incorrect absorption for some drug BCS classes (class IIa, for example), (d) GITs size variability among population, (e) incorrectly predicting the absorption of drugs that are GIT target specific, and (f) erroneous mixing in the domain. In this study, we have developed a multiscale absorption and transit (MAT) toolkit to simulate the dissolution, transport, absorption, distribution, metabolism, and elimination of orally administered drugs in the human GIT at multiple levels. MAT was constructed by integrating the spatially accurate first-principles driven high-fidelity drug transport, dissolution, and absorption model in the human stomach and GIT using our recently published quasi-3D (Q3D) framework. The process integrated the multilayer intestine physiologically based pharmacokinetics models with the whole-body compartmental models to predict the systemic pharmacokinetics of oral drugs. The computational results showed that this multiscale tool was able to match the experimental concentration results (individual and population) better than the traditional compartmental models. Ultimately, MAT will be developed into a commercial product to meet urgent demands from pharmaceutical and biomedical industries.

A Review of Respiratory Anatomical Development, Air Flow Characterization and Particle Deposition

The understanding of complex inhalation and transport processes of pollutant particles through the human respiratory system is important for investigations into dosimetry and respiratory health effects in various settings, such as environmental or occupational health. The studies over the last few decades for micro- and nanoparticle transport and deposition have advanced the understanding of drug-aerosol impacts in the mouth-throat and the upper airways. However, most of the Lagrangian and Eulerian studies have utilized the non-realistic symmetric anatomical model for airflow and particle deposition predictions. Recent improvements to visualization techniques using high-resolution computed tomography (CT) data and the resultant development of three dimensional (3-D) anatomical models support the realistic representation of lung geometry. Yet, the selection of different modelling approaches to analyze the transitional flow behavior and the use of different inlet and outlet conditions provide a dissimilar prediction of particle deposition in the human lung. Moreover, incorporation of relevant physical and appropriate boundary conditions are important factors to consider for the more accurate prediction of transitional flow and particle transport in human lung. This review critically appraises currently available literature on airflow and particle transport mechanism in the lungs, as well as numerical simulations with the aim to explore processes involved. Numerical studies found that both the Euler–Lagrange (E-L) and Euler–Euler methods do not influence nanoparticle (particle diameter ≤50 nm) deposition patterns at a flow rate ≤25 L/min. Furthermore, numerical studies demonstrated that turbulence dispersion does not significantly affect nanoparticle deposition patterns. This critical review aims to develop the field and increase the state-of-the-art in human lung modelling.

Numerical modeling of particle deposition in the conducting airways of asthmatic children

Mounting evidence has linked long- and short-term exposure to particulate air pollution with the incidence and exacerbation of asthma in children, but the biological pathogenesis is unclear. We examined the deposition of particles in the airways of asthmatic children. A planar and symmetric model of airways for 4-year-old asthmatic children was considered. Airflow and particle deposition in the upper (G3-G6) and lower (G9-G12) conducting airways were numerically investigated using computation fluid dynamics (CFD) method. We considered the manifestation of moderate (30% reduction in airway diameter) and severe (60% reduction) asthma. Micron particles (1-10 µm) were considered. We found that particle deposition in the asthmatic children was significantly higher than that in healthy children. The deposition efficiency increased slowly with particle size for healthy children, but increased rapidly for asthmatic children, such that smaller particles could be deposited in the conducting airways of asthmatics. For healthy children, particles were deposited by inertial impaction and gravitational sedimentation respectively in the upper and lower airways, but deposited by inertial impaction in asthmatic children. The severity of the asthma increased the particle deposition in the airways. Our study indicated that asthmatic children were more susceptible to the effect of particulate air pollution. The constricted airways increased the particle deposition by inertial impaction, which may be the biological pathogenesis that causes the hospitalization of asthma in children. Avoiding exposure during air pollution events will be an effective measure to reduce the asthma attack.

Euler-Lagrange Prediction of Diesel-Exhaust Polydisperse Particle Transport and Deposition in Lung: Anatomy and Turbulence Effects

In clinical assessments, the correlation between atmospheric air pollution and respiratory damage is highly complicated. Epidemiological studies show that atmospheric air pollution is largely responsible for the global proliferation of pulmonary disease. This is particularly significant, since most Computational Fluid Dynamics (CFD) studies to date have used monodisperse particles, which may not accurately reflect realistic inhalation patterns, since atmospheric aerosols are mostly polydisperse. The aim of this study is to investigate the anatomy and turbulent effects on polydisperse particle transport and deposition (TD) in the upper airways. The Euler-Lagrange approach is used for polydisperse particle TD prediction in both laminar and turbulent conditions. Various anatomical models are adopted to investigate the polydisperse particle TD under different flow conditions. Rossin-Rammler diameter distribution is used for the distribution of the initial particle diameter. The numerical results illustrate that airflow rate distribution at the right lung of a realistic model is higher than a non-realistic model. The CFD study also shows that turbulence effects on deposition are higher for larger diameter particles than with particles of smaller diameter. A significant amount of polydisperse particles are also shown to be deposited at the tracheal wall for CT-based model, whereas particles are mostly deposited at the carinal angle for the non-realistic model. A comprehensive, polydisperse particle TD analysis would enhance understanding of the realistic deposition pattern and decrease unwanted therapeutic aerosol deposition at the extrathoracic airways.

Implementation of a specific boundary condition for a simplified symmetric single-path CFD lung model with OpenFOAM

CFD modeling research about the lung airflow with a complete resolution and an adequate accuracy at all scales requires a great amount of computational resources due to the vast number of necessary grid elements. As a result, a common practice is to conduct simplifications that allows to manage it with ordinary computational power. In this study, the implementation of a special boundary condition in order to develop a simplified single conductive lung airway model, which exactly represents the effect of the removed airways, is presented. The boundary condition is programmed in the open-source software OpenFOAM®, and the developed source code is presented in the proper syntax. After this description, modeling accuracy is evaluated under different flow rate conditions typical of human breathing processes, including both inspiration and expiration movements. Afterward, a validation process is conducted using results of a Weibel's model (0-4 generations) simulation for a medium flow rate of 50 L/min. Finally, a comparison against the proposed boundary condition implemented in the commercial code ANSYS Fluent is made, which highlights the benefits of using the free code toolbox. The specific contribution of this paper will be to show that OpenFOAM® developed model can perform even better than other commercial codes due to a precise implementation and coupling of the default solver with the in-house functions by virtue of the open-source nature of the code.

In Silico Methods for Development of Generic Drug-Device Combination Orally Inhaled Drug Products

The development of generic, single‐entity, drug–device combination products for orally inhaled drug products is challenging in part because of the complex nature of device design characteristics and the difficulties associated with establishing bioequivalence for a locally acting drug product delivered to the site of action in the lung. This review examines in silico models that may be used to support the development of generic orally inhaled drug products and how model credibility may be assessed.

Numerical simulation of magnetic drug targeting to a tumor in the simplified model of the human lung

BACKGROUND

Magnetic drug targeting improves effectiveness of medicine application and reduces its side effects. In this method, drugs with magnetic core are released in the lung and they are steered towards the tumor by applying an external magnetic field. A number of researchers utilized numerical methods to study particle deposition in the lung, but magnetic drug delivery to the tumors in the human lung has not been addressed yet.

METHOD

In the present study, Weibel model is used for human airway geometry from generation G0-G3. Moreover, a tumor is considered in the lung, which is located in G2. Particles are made of iron oxide magnetic cores and poly lactic coglycolic acid shells. Fluid flow is assumed laminar and particles are coupled with the fluid by one-way method. The magnetic field is produced by a coil with law current intensities instead of a wire with high current intensities. Influences of various parameters such as particle diameter, magnetic source position, current intensity, and inlet mass flow rate and tumor size on the deposition efficiency on the tumor surface are reported.

RESULTS

Results show that magnetic drug targeting enhances deposition efficiency on the tumor surface Furthermore, when the current intensity rises from 10 (A) to 20 (A), tumor enlarging, and increasing particle diameter, lead to deposition efficiency enhancement, but efficiency decreases by increasing mass flow rate. However, when current intensity is 20 (A), deposition efficiency decreases in two situations. The first situation is when mass flow rate is 7 (L/min) and particle diameter is 9 (µm), and the second one is in 10 (L/min) mass flow rate and 9 (µm) diameter.

CONCLUSION

The results demonstrated that magnetic drug targeting is applicable and suitable for all tumors specially for small tumors (r/R = 0.5 in this case) that efficiency increase from 0% in the absence of magnetic field to more than 2% in the presence of magnetic field.

Innovation for Generic Drugs: Science and Research Under the Generic Drug User Fee Amendments of 2012

Regulatory science is science and research intended to improve decision making in a regulatory framework. Improvements in decision making can be in both accuracy (making better decisions) and in efficiency (making faster decisions). Science and research supported by the Generic Drug User Fee Amendments of 2012 (GDUFA) have focused on two innovative methodologies that work together to enable new approaches to development and review of generic drugs: quantitative models and advanced in vitro product characterization. Quantitative models faithfully represent current scientific understanding. They are tools pharmaceutical scientists and clinical pharmacologists use for making better and faster product development decisions. Advances in the in vitro product comparisons provide the measurements of product differences that are the critical input into the models. This paper outlines four areas where science and research funded by GDUFA support synergistic use of models and characterization at critical decision points during generic drug product development and review.

Human Stimulus Factor Is a Promising Peptide for Delivery of Therapeutics

Fluticasone propionate uptake in the presence of a proprietary cell-penetrating peptide (human stimulus factor, [HSF]) based on the N-terminal domain of lactoferrin was studied, alone and in combination with salmeterol, using an air interface Calu-3 epithelial model. The HSF enhanced uptake and transport of fluticasone propionate across the epithelial barrier when alone and in presence of salmeterol. This was attributed to transcellular-mediated uptake. This HSF is a promising peptide for delivery of therapeutics where enhanced epithelial penetrating is required.

Polydisperse Microparticle Transport and Deposition to the Terminal Bronchioles in a Heterogeneous Vasculature Tree

The atmospheric particles from different sources, and the therapeutic particles from various drug delivery devices, exhibit a complex size distribution, and the particles are mostly polydisperse. The limited available in vitro, and the wide range of in silico models have improved understanding of the relationship between monodisperse particle deposition and therapeutic aerosol transport. However, comprehensive polydisperse transport and deposition (TD) data for the terminal airways is still unavailable. Therefore, to benefit future drug therapeutics, the present numerical model illustrates detailed polydisperse particle TD in the terminal bronchioles for the first time. Euler-Lagrange approach and Rosin-Rammler diameter distribution is used for polydisperse particles. The numerical results show higher deposition efficiency (DE) in the right lung. Specifically, the larger the particle diameter (d_p > 5 μm), the higher the DE at the bifurcation area of the upper airways is, whereas for the smaller particle (d_p < 5 μm), the DE is higher at the bifurcation wall. The overall deposition pattern shows a different deposition hot spot for different diameter particle. These comprehensive lobe-specific polydisperse particle deposition studies will increase understanding of actual inhalation for particle TD, which could potentially increase the efficiency of pharmaceutical aerosol delivery at the targeted position of the terminal airways.

A Quasi-3D compartmental multi-scale approach to detect and quantify diseased regional lung constriction using spirometry data

Spirometry is a widely used pulmonary function test to detect the airflow limitations associated with various obstructive lung diseases, such as asthma, chronic obstructive pulmonary disease, and even obesity-related complications. These conditions arise due to the change in the airway resistance, alveolar compliance, and inductance values. Currently, zero-dimensional compartmental models are commonly used for calibrating these resistance, compliance, and inductance values, ie, solving the inverse spirometry problem. However, zero-dimensional compartments cannot capture the flow physics or the spatial geometry effects, thereby generating a low fidelity prediction of the diseased lung. Computational fluid dynamics (CFD) models offer higher fidelity solutions but may be impractical for certain applications due to the duration of these simulations. Recently, a novel, fast-running, and robust Quasi-3D (Q3D) wire model for simulating the airflow in the human lung airway was developed by CFD Research Corporation. This Q3D method preserved the 3D spatial nature of the airways and was favorably validated against CFD solutions. In the present study, the Q3D compartmental multi-scale combination is further improved to predict regional lung constriction of diseased lungs using spirometry data. The Q3D mesh is resolved up to the eighth lung airway generation. The remainder of the airways and the alveoli sections are modeled using a compartmental approach. The Q3D geometry is then split into different spatial sections, and the resistance values in these regions are obtained using parameter inversion. Finally, the airway diameter values are then reduced to create the actual diseased lung model, corresponding to these resistance values. This diseased lung model can be used for patient-specific drug deposition predictions and the subsequent optimization of the orally inhaled drug products.

A compartment-quasi-3D multiscale approach for drug absorption, transport, and retention in the human lungs

Most current models used for modeling the pulmonary drug absorption, transport, and retention are 0D compartmental models where the airways are generally split into the airways and alveolar sections. Such block models deliver low fidelity solutions and the spatial lung drug concentrations cannot be obtained. Other approaches use high fidelity CFD models with limited capabilities due to their exorbitant computational cost. Recently, we presented a novel, fast-running and robust quasi-3D (Q3D) model for modeling the pulmonary airflow. This Q3D method preserved the 3D lung geometry, delivered extremely accurate solutions, and was 25 000 times faster in comparison to the CFD methods. In this paper, we present a Q3D-compartment multiscale combination to model the pulmonary drug absorption, transport, and retention. The initial deposition is obtained from CFD simulations. The lung absorption compartment model of Yu and Rosania is adapted to this multiscale format. The lung is modeled in the Q3D format till the eighth airway generation. The remainder of the lung along with the systemic circulation and elimination processes was modeled using compartments. The Q3D model is further adapted, by allowing for various heterogeneous annular lung layers. This allows us to model the drug transport across the layers and along the lung. Using this multiscale model, the spatiotemporal drug concentrations in the different lung layers and the temporal concentration in the plasma are obtained. The concentration profile in the plasma was found to be better aligned with the experimental findings in comparison with compartmental model for the standard test cases. Thus, this multiscale model can be used to optimize the target-specific drug delivery and increase the localized bioavailability, thereby facilitating applications from the bench to bedside for various patient/lung-disease variations.

The prediction of viscous losses and pressure drop in models of the human airways

This paper examines the viscous flow resistance in branching tubes as applied to simplified models of the lungs and compares the results of computational fluid dynamics simulations for a range of conditions with measurement data. The results are in good agreement with the available measurement data for both inspiration and expiration. A detailed sensitivity analysis of the dissipation and viscous resistance in a branch then examines the ratio of the viscous resistance to that for a fully developed Poiseuille flow, Z. As other researchers have noted, the calculated resistances give lower values than those from the standard correlation of Pedley et al. The results demonstrate that the resistance is sensitive to the velocity profile upstream of the bifurcations and explain from fluid dynamical considerations the apparent sensitivity of the resistance to the generation number of the branch. The paper also suggests a revised value for the calibration constant in the expression for Z. Finally, a limited set of results are presented for junction losses, and for expiration.

Robust nondimensional estimators to assess the nasal airflow in health and disease

There are significant variations of both human nose shapes and airflow patterns inside nasal cavities, so it is difficult to provide a comprehensive medical identification using a universal template for what otolaryngologists consider normal breathing at rest. In addition, airflow patterns present even more random characteristics in diseased nasal cavities. To give a medical assessment to differentiate the nasal cavities in health and disease, we propose 2 nondimensional estimators obtained from both medical images and computational fluid dynamics. The first mathematical estimator ϕ is a function of geometric features and potential asymmetries between nasal passages, while the second estimator R represents in fluid mechanics terms the total nasal resistance that corresponds to the atmosphere-choana pressure drop. These estimators only require global information such as nasal geometry and magnitudes of flow determined by simulations under laminar conditions. We find that these estimators take low and high values for healthy and diseased nasal cavities, respectively. Our study, based on 24 healthy and 25 diseased Caucasian subjects, reveals that there is an interval of values associated with healthy cavities that clusters in a small region of the plane ϕ-R. Therefore, these estimators can be seen as a first approximation to provide nasal airflow data to the clinician in a noninvasive method, as the computed tomography scan that provides the required images is routinely obtained as a result of the preexisting naso-sinusal condition.

Simulation of the human airways using virtual topology tools and meshing optimization

A method is proposed to improve the quality of the three-dimensional airway geometric models using a commercial software, checking the number of elements, meshing time, and aspect ratio and skewness parameters. The use of real and virtual topologies combined with patch-conforming and patch-independent meshing algorithms results in four different models being the best solution the combination of virtual topology and patch-independent algorithm, due to an excellent aspect ratio and skewness of the elements, and minimum meshing time. The result is a reduction in the computational time required for both meshing and simulation due to a smaller number of cells. The use of virtual topologies combined with patch-independent meshing algorithms could be extended in bioengineering because the geometries handling is similar to this case. The method is applied to a healthy person using their computed tomography images. The resulting numerical models are able to simulate correctly a forced spirometry.

Structure and functional impact of seed region variant in MIR-499 gene family in bronchial asthma

BACKGROUND

Small non-coding RNAs (microRNAs) have been evolved to master numerous cellular processes. Genetic variants within microRNA seed region might influence microRNA biogenesis and function. The study aimed at determining the role of microRNA-499 (MIR-499) gene family polymorphism as a marker for susceptibility and progression of bronchial asthma and to analyze the structural and functional impact of rs3746444 within the seed region.

METHODS

Genotyping for 192 participants (96 patients and 96 controls) in the discovery phase and 319 subjects (115 patients and 204 controls) in the replication phase was performed via Real Time-Polymerase Chain Reaction technology. Patients underwent the methacholine challenge test and biochemical analysis. Gene structural and functional analysis, target prediction, annotation clustering, and pathway enrichment analysis were executed. Predicted functional effect of rs37464443 SNP was analyzed.

RESULTS

miR-499 gene family is highly implicated in inflammation-related signaling pathways. Rs374644 (A > G) in MIR499A and MIR499B within the seed region could disrupt target genes and create new genes. The G variant was associated with high risk of developing asthma under all genetic association models (G versus A: OR = 3.27, 95% CI = 2.53-4.22; GG versus AA: OR = 9.52, 95% CI = 5.61-16.5; AG versus AA: OR = 2.13, 95% CI = 1.24-3.46; GG + AG versus AA: OR = 4.43, 95% CI = 2.88-6.82). GG genotype was associated with poor pre-bronchodilator FEV1 (p = 0.047) and the worst bronchodilator response after Salbutamol inhalation, represented in low peaked expiratory flow rate (p = 0.035).

CONCLUSIONS

miR-499 rs3746444 (A > G) polymorphism was associated with asthma susceptibility and bronchodilator response in Egyptian children and adolescents. Further functional analysis is warranted to develop more specific theranostic agents for selecting targeted therapy.

β2 adrenergic agonist suppresses eosinophil-induced epithelial-to-mesenchymal transition of bronchial epithelial cells

Background

Epithelial-mesenchymal transition is currently recognized as an important mechanism for the increased number of myofibroblasts in cancer and fibrotic diseases. We have already reported that epithelial-mesenchymal transition is involved in airway remodeling induced by eosinophils. Procaterol is a selective and full β₂ adrenergic agonist that is used as a rescue of asthmatic attack inhaler form and orally as a controller. In this study, we evaluated whether procaterol can suppress epithelial-mesenchymal transition of airway epithelial cells induced by eosinophils.

Methods

Epithelial-mesenchymal transition was assessed using a co-culture system of human bronchial epithelial cells and primary human eosinophils or an eosinophilic leukemia cell line.

Results

Procaterol significantly inhibited co-culture associated morphological changes of bronchial epithelial cells, decreased the expression of vimentin, and increased the expression of E-cadherin compared to control. Butoxamine, a specific β₂-adrenergic antagonist, significantly blocked changes induced by procaterol. In addition, procaterol inhibited the expression of adhesion molecules induced during the interaction between eosinophils and bronchial epithelial cells, suggesting the involvement of adhesion molecules in the process of epithelial-mesenchymal transition. Forskolin, a cyclic adenosine monophosphate-promoting agent, exhibits similar inhibitory activity of procaterol.

Conclusions

Overall, these observations support the beneficial effect of procaterol on airway remodeling frequently associated with chronic obstructive pulmonary diseases.

Combination of glycopyrronium and indacaterol inhibits carbachol-induced ERK5 signal in fibrotic processes

Background

Airway fibrosis is one of the pathological features of chronic obstructive pulmonary disease (COPD), and recent studies revealed that acetylcholine plays an important role in the development of airway remodeling by stimulating proliferation and collagen synthesis of lung fibroblasts. This study was designed to examine the effects of a long-acting muscarinic receptor antagonist (LAMA) glycopyrronium and a long-acting β2 adrenergic receptor agonist (LABA) indacaterol on acetylcholine-mediated fibrotic responses in lung fibroblasts.

Methods

After carbachol (CCh) or transforming growth factor-β1 (TGF-β1) exposure, the response to glycopyrronium and indacaterol was determined in vitro in fibroblasts isolated from mild-to-moderate COPD lung tissue. The ability of fibroblasts to mediate the contraction of collagen gels was assessed. The expression of α-smooth muscle actin (α-SMA) and the phosphorylation of extracellular-signal-regulated kinase 5 (ERK5) were determined by immunoblot. TGF-β1 was quantified by ELISA and acetylcholine was quantified by liquid chromatography tandem-mass spectrometry.

Results

CCh stimulated fibroblast-mediated collagen gel contraction and α-SMA expression and TGF-β1 release by fibroblasts. Blockade of autocrine TGF-β1 attenuated CCh-mediated fibrotic responses, while TGF-β1 did not stimulate acetylcholine release. Glycopyrronium plus indacaterol significantly attenuated CCh- and TGF-β1-mediated fibrotic responses through inhibition of ERK5 phosphorylation. Notably, the magnitudes of CCh- and TGF-β1-stimulated gel contraction, CCh-induced TGF-β1 release, and ERK5 phosphorylation were greater in fibroblasts isolated from COPD subjects than in those from non-smokers.

Conclusions

CCh induced TGF-β1 self-sustaining signaling loops by potentiating ERK5 signaling and promoted myofibroblast activity. This autocrine signaling mechanism may be an attractive therapeutic target to block the fibrotic response, which was modulated by the combination of glycopyrronium and indacaterol.