The effect of lung emptying before the inhalation of aerosol drugs on drug deposition in the respiratory system.

The amount of drug depositing in the airways depends, among others, on the inhalation manoeuvre and breathing parameters. The objective of this study was to quantify the effect of lung emptying before the inhalation of drugs on the lung doses. Thirty healthy adults were recruited. Their breathing profiles were recorded while inhaling through six different emptied DPI devices without breathe-out and after comfortable or forced exhalation. The corresponding emitted doses and aerosol size distributions were derived from the literature. The Stochastic Lung Model was used to estimate the deposited doses. In general, forceful exhalation caused increased flow rate and inhaled air volume. Increased flow rate led to the increase of the average lung dose for drugs with positive lung dose-flow rate correlation (e.g. Symbicort®: relative increase of 6.7%, Bufomix®: relative increase of 9.2%). For drugs with negative correlation of lung dose with flow rate (all the studied drugs except the above two) lung emptying caused increased (Foster® by 2.7%), almost unchanged (Seebri®, Relvar®, Bretaris®) and also decreased (Onbrez® by 6.6%) average lung dose. It is worth noting that there were significant inter-individual differences, and lung dose of each drug could be increased by a number of subjects. In conclusion, the change of lung dose depends on the degree of lung emptying, but it is also inhaler and drug specific. Forceful exhalation can help in increasing the lung dose only if the above specificities are taken into account.

Modeling of pulmonary deposition of agents of open and fixed dose triple combination therapies through two different low-resistance inhalers in COPD: a pilot study.

Introduction: Inhalation therapy is a cornerstone of treating patients with chronic obstructive pulmonary disease (COPD). Inhaler devices might influence the effectiveness of inhalation therapy. We aimed to model and compare the deposition of acting agents of an open and a fixed dose combination (FDC) triple therapy and examine their repeatability. Methods: We recruited control subjects (Controls, n = 17) and patients with stable COPD (S-COPD, n = 13) and those during an acute exacerbation (AE-COPD, n = 12). Standard spirometry was followed by through-device inhalation maneuvers using a pressurized metered dose inhaler (pMDI) and a soft mist inhaler (SMI) to calculate deposition of fixed dose and open triple combination therapies by numerical modeling. Through-device inspiratory vital capacity (IVCd) and peak inspiratory flow (PIFd), as well as inhalation time (tin) and breath hold time (tbh) were used to calculate pulmonary (PD) and extrathoracic deposition (ETD) values. Deposition was calculated from two different inhalation maneuvers. Results: There was no difference in forced expiratory volume in 1 s (FEV1) between patients (S-COPD: 42 ± 5% vs. AE-COPD: 35 ± 5% predicted). Spiriva® Respimat® showed significantly higher PD and lower ETD values in all COPD patients and Controls compared with the two pMDIs. For Foster® pMDI and Trimbow® pMDI similar PD were observed in Controls, while ETD between Controls and AE-COPD patients did significantly differ. There was no difference between COPD groups regarding the repeatability of calculated deposition values. Ranking the different inhalers by differences between the two deposition values calculated from separate maneuvers, Respimat® produced the smallest inter-measurement differences for PD. Discussion: Our study is the first to model and compare PD using pMDIs and an SMI as triple combination in COPD. In conclusion, switching from FDC to open triple therapy in cases when adherence to devices is maintanined may contribute to better therapeutic effectiveness in individual cases using low resistance inhalers.

Modeling of nursing care-associated airborne transmission of SARS-CoV-2 in a real-world hospital setting.

Respiratory transmission of SARS-CoV-2 from one older patient to another by airborne mechanisms in hospital and nursing home settings represents an important health challenge during the COVID-19 pandemic. However, the factors that influence the concentration of respiratory droplets and aerosols that potentially contribute to hospital- and nursing care-associated transmission of SARS-CoV-2 are not well understood. To assess the effect of health care professional (HCP) and patient activity on size and concentration of airborne particles, an optical particle counter was placed (for 24 h) in the head position of an empty bed in the hospital room of a patient admitted from the nursing home with confirmed COVID-19. The type and duration of the activity, as well as the number of HCPs providing patient care, were recorded. Concentration changes associated with specific activities were determined, and airway deposition modeling was performed using these data. Thirty-one activities were recorded, and six representative ones were selected for deposition modeling, including patient's activities (coughing, movements, etc.), diagnostic and therapeutic interventions (e.g., diagnostic tests and drug administration), as well as nursing patient care (e.g., bedding and hygiene). The increase in particle concentration of all sizes was sensitive to the type of activity. Increases in supermicron particle concentration were associated with the number of HCPs (r = 0.66; p < 0.05) and the duration of activity (r = 0.82; p < 0.05), while submicron particles increased with all activities, mainly during the daytime. Based on simulations, the number of particles deposited in unit time was the highest in the acinar region, while deposition density rate (number/cm2/min) was the highest in the upper airways. In conclusion, even short periods of HCP-patient interaction and minimal patient activity in a hospital room or nursing home bedroom may significantly increase the concentration of submicron particles mainly depositing in the acinar regions, while mainly nursing activities increase the concentration of supermicron particles depositing in larger airways of the adjacent bed patient. Our data emphasize the need for effective interventions to limit hospital- and nursing care-associated transmission of SARS-CoV-2 and other respiratory pathogens (including viral pathogens, such as rhinoviruses, respiratory syncytial virus, influenza virus, parainfluenza virus and adenoviruses, and bacterial and fungal pathogens).

Effects of hygroscopic growth of ambient urban aerosol particles on their modelled regional and local deposition in healthy and COPD-compromised human respiratory system.

Total, regional and local deposition fractions of urban-type aerosol particles with diameters of 50, 75, 110 and 145 nm were modelled and studied in their dry state and after their hygroscopic growth using a Stochastic Lung Model and a Computational Fluid and Particle Dynamics method. Healthy subjects and patients with severe chronic obstructive pulmonary disease (COPD) were considered. The hygroscopic growth factors (HGFs) adopted were determined experimentally and represent a real urban-type environment. The hygroscopic growth of particles resulted in decrease of the deposition fractions in all major parts of the healthy respiratory system and the extent of the deposited fractions was rising monotonically with particle size. In the extrathoracic (ET) region, the relative decrease was between 7% and 13%. In the lungs the deposition decreased by 11-16%. The decrease of deposition fraction due to hygroscopic growth was more accentuated in the conductive airways (up to 25%) and less pronounced towards the terminal airways. The spatial distribution of the deposited particles remained highly inhomogeneous with some areas containing thousands times more particles than the average number of particles per unit surface area. For COPD patients, the hygroscopic growth produced similar deposition alterations in the ET region than for healthy subjects. In the conductive airways, however, the particle growth caused a substantial relative decrease in the deposition fractions. In contrast, the relative depositions of hygroscopic particles increased in the acinar region.

Ultrafine urban particle measurements in Budapest and their airway deposition distribution calculation.

OBJECTIVES: The aim of this study was to provide particle number and mass deposition rates of submicron particles in the human airways as inputs for toxicology and other areas of aerosol science. METHODS: Scanning Mobility Particle Spectrometer was used to measure the number concentrations and size distributions of the ultrafine urban particles during summer and winter in Budapest. The Stochastic Lung Model (SLM) was applied to calculate number and mass deposition rates of the inhaled particles in different anatomical regions of the airways. RESULTS: Our calculations revealed that for the selected days in summer and winter with PM10 values below the health limit 4.7 and 18.4 billion particles deposited in the bronchial region of the lungs. The deposition in the acinar region of the lung was even higher, 8.3 billion particles for the summer day, and 33.8 billion particles for winter day. CONCLUSIONS: Our results clearly demonstrate that large daily numbers of urban UFPs are deposited in the respiratory tract, which may play a key role in the health effects of particulate matter (PM) inhalation. Present results, connecting the ambient exposure parameters with the local burden of the airway epithelium, can be useful inputs of in vitro cell culture experiments. By the combination of urban UFP monitoring and numerical modeling of particle deposition with toxicological studies, the health risks of urban aerosols could be better assessed. The use of UFP data in addition to PM10 and PM2.5 in the epidemiological studies would also be indicated.

Deposition distribution of the new coronavirus (SARS-CoV-2) in the human airways upon exposure to cough-generated droplets and aerosol particles.

The new coronavirus disease 2019 (COVID-19) has been emerged as a rapidly spreading pandemic. The disease is thought to spread mainly from person-to-person through respiratory droplets produced when an infected person coughs, sneezes, or talks. The pathogen of COVID-19 is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It infects the cells binding to the angiotensin-converting enzyme 2 receptor (ACE2) which is expressed by cells throughout the airways as targets for cellular entry. Although the majority of persons infected with SARS-CoV-2 experience symptoms of mild upper respiratory tract infection, in some people infections of the acinar airways result in severe, potentially fatal pneumonia. However, the induction of COVID-19 pneumonia requires that SARS-CoV-2 reaches the acinar airways. While huge efforts have been made to understand the spread of the disease as well as the pathogenesis following cellular entry, much less attention is paid to how SARS-CoV-2 from the environment reach the receptors of the target cells. The aim of the present study is to characterize the deposition distribution of SARS-CoV-2 in the airways upon exposure to cough-generated droplets and aerosol particles. For this purpose, the Stochastic Lung Deposition Model has been applied. Particle size distribution, breathing parameters supposing normal breathing through the nose, and viral loads were taken from the literature. We found that the probability of direct infection of the acinar airways due to inhalation of particles emitted by a bystander cough is very low. As the number of viruses deposited in the extrathoracic airways is about 7 times higher than in the acinar airways, we concluded that in most cases COVID-19 pneumonia must be preceded by SARS-CoV-2 infection of the upper airways. Our results suggest that without the enhancement of viral load in the upper airways, COVID-19 would be much less dangerous. The period between the onset of initial symptoms and the potential clinical deterioration could provide an opportunity for prevention of pneumonia by blocking or significantly reducing the transport of viruses towards the acinar airways. Therefore, even non-specific treatment forms like disinfection of the throat and nasal and oral mucosa may effectively keep the viral load of the upper airways low enough to avoid or prolong the progression of the disease. In addition, using a tissue or cloth in order to absorb droplets and aerosol particles emitted by own coughs of infected patients before re-inhalation is highly recommended even if they are alone in quarantine.

The degree of inhomogeneity of the absorbed cell nucleus doses in the bronchial region of the human respiratory tract.

Inhalation of short-lived radon progeny is an important cause of lung cancer. To characterize the absorbed doses in the bronchial region of the airways due to inhaled radon progeny, mostly regional lung deposition models, like the Human Respiratory Tract Model (HRTM) of the International Commission on Radiological Protection, are used. However, in this model the site specificity of radiation burden in the airways due to deposition and fast airway clearance of radon progeny is not described. Therefore, in the present study, the Radact version of the stochastic lung model was used to quantify the cellular radiation dose distribution at airway generation level and to simulate the kinetics of the deposited radon progeny resulting from the moving mucus layer. All simulations were performed assuming an isotope ratio typical for an average dwelling, and breathing mode characteristic of a healthy adult sitting man. The study demonstrates that the cell nuclei receiving high doses are non-uniformly distributed within the bronchial airway generations. The results revealed that the maximum of the radiation burden is at the first few bronchial airway generations of the respiratory tract, where most of the lung carcinomas of former uranium miners were found. Based on the results of the present simulations, it can be stated that regional lung models may not be fully adequate to describe the radiation burden due to radon progeny. A more realistic and precise calculation of the absorbed doses from the decay of radon progeny to the lung requires deposition and clearance to be simulated by realistic models of airway generations.

Comparison of airway deposition distributions of particles in healthy and diseased workers in an Egyptian industrial site.

The objective of this study is the prediction and comparison of airway deposition patterns of an industrial aerosol in healthy workers and workers suffering from silicosis. Mass concentrations and related size distributions of particulate matter were measured in the industrial area of Samalut in Minia, Egypt. A novel stochastic lung deposition model, simulating the symptoms of silicosis by chronic bronchial (Br) obstruction and emphysema in the acinar (Ac) region, was applied to compute mass deposition fractions, deposition density, deposition rate and deposition density rate distributions in healthy and diseased workers. In the case of healthy workers, both mass deposition fractions and deposition rates are highest in the first half of the Ac region of the lung, while the corresponding deposition density and deposition density rate distributions exhibit a maximum in the large Br airways. In the case of diseased lungs, bullous emphysema causes a large deposition peak in the region of the bronchioli respiratorii. Regional mass deposition fractions adopt maximum values in the extrathoracic region, except during mouth breathing for bullous emphysema, where Ac deposition can be the most prominent. In general, lung deposition is significantly higher in diseased than in healthy lungs. Indeed, workers suffering from silicosis receive significantly higher Ac doses than healthy workers exposed to the same aerosol. Thus, this illness may progress faster if a diseased worker remains in a strongly polluted area.

Numerical simulation of emitted particle characteristics and airway deposition distribution of Symbicort(®) Turbuhaler(®) dry powder fixed combination aerosol drug.

One of the most widespread dry powder fixed combinations used in asthma and chronic obstructive pulmonary disease (COPD) management is Symbicort(®) Turbuhaler(®). The aim of this study was to simulate the deposition distribution of both components of this drug within the airways based on realistic airflow measurements. Breathing parameters of 25 healthy adults (11 females and 14 males) were acquired while inhaling through Turbuhaler(®). Individual specific emitted doses and particle size distributions of Symbicort(®) Turbuhaler(®) were determined. A self-developed particle deposition model was adapted and validated to simulate the deposition of budesonide (inhaled corticosteroid; ICS) and formoterol (long acting ß2 agonist; LABA) in the upper airways and lungs of the healthy volunteers. Based on current simulations the emitted doses varied between 50.4% and 92.5% of the metered dose for the ICS, and between 38% and 96.1% in case of LABA component depending on the individual inhalation flow rate. This variability induced a notable inter-individual spread of the deposited lung doses (mean: 33.6%, range: 20.4%-48.8% for budesonide and mean: 29.8%, range: 16.4%-42.9% for formoterol). Significant inter-gender differences were also observed. Average lung dose of budesonide was 29.2% of the metered dose for females and 37% for males, while formoterol deposited with 26.4% efficiency for females and 32.5% for males. Present results also highlighted the importance of breath-holding after inhalation of the drug. About a half of the total lung deposition occurred during breath-hold at 9.6s average breath-hold time. Calculated depositions confirmed appropriate lung deposition of Symbicort(®) Turbuhaler(®) for both genders, however more effort for optimal inhalation technique is advised for persons with low vital capacity. This study demonstrated the possibility of personalized prediction of airway deposition of aerosol drugs by numerical simulations. The methodology developed in this study will be applicable also to other marketed drugs in the future.

Computer modeling of airway deposition distribution of Foster(®) NEXThaler(®) and Seretide(®) Diskus(®) dry powder combination drugs.

Asthma is a serious global health problem with rising prevalence and treatment costs. Due to the growing number of different types of inhalation devices and aerosol drugs, physicians often face difficulties in choosing the right medication for their patients. The main objectives of this study are (i) to elucidate the possibility and the advantages of the application of numerical modeling techniques in aerosol drug and device selection, and (ii) to demonstrate the possibility of the optimization of inhalation modes in asthma therapy with a numerical lung model by simulating patient-specific drug deposition distributions. In this study we measured inhalation parameter values of 25 healthy adult volunteers when using Foster(®) NEXThaler(®) and Seretide(®) Diskus(®). Relationships between emitted doses and patient-specific inhalation flow rates were established. Furthermore, individualized emitted particle size distributions were determined applying size distributions at measured flow rates. Based on the measured breathing parameter values, we calculated patient-specific drug deposition distributions for the active components (steroid and bronchodilator) of both drugs by the help of a validated aerosol lung deposition model adapted to therapeutic aerosols. Deposited dose fractions and deposition densities have been computed in the entire respiratory tract, in distinct anatomical regions of the airways and at the level of airway generations. We found that Foster(®) NEXThaler(®) deposits more efficiently in the lungs (average deposited steroid dose: 42.32±5.76% of the nominal emitted dose) than Seretide(®) Diskus(®) (average deposited steroid dose: 24.33±2.83% of the nominal emitted dose), but the variance of the deposition values of different individuals in the lung is significant. In addition, there are differences in the required minimal flow rates, therefore at certain patients Seretide(®) Diskus(®) or pMDIs could be a better choice. Our results show that validated computer deposition models could be useful tools in providing valuable deposition data and assisting health professionals in the personalized drug selection and delivery optimization. Patient-specific modeling could open a new horizon in the treatment of asthma towards a more effective personalized medicine in the future.