Evaluating Drug Deposition Patterns from Turbuhaler® in Healthy and Diseased Lung Models of Preschool Children.

The efficacy of pediatric oral drug delivery using dry powder inhalers, such as Turbuhaler®, is dependent on the age and health of the test subjects. The available clinical data for these studies is scant and rarely provide correlations between the health condition and the regional lung deposition. In particular, the data and the correlations for pre-school children are minimal. Deposition simulations were performed using the newly developed Quasi-3D whole lung model to analyze the effect of health conditions on the regional lung deposition from the Turbuhaler® in 3-year-old children. The healthy lung model was created from CT scan data. Cystic-fibrosis models were created by uniformly constricting the airways to various degrees. The simulated drug deposition outcomes were validated against the available experimental data. The results show that, while the dose deposited in the lungs exhibits minor variations, the Peripheral:Central (P/C) ratio is strongly affected by both the health condition and the inflow variations. The above ratio is reduced by ~30% for the severely diseased case, compared to its healthy counterpart, for the same inhalation profile. This indicates that lower doses reach the peripheral lung, in pediatric cystic-fibrosis subjects, thus requiring a larger therapeutic dose.

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.

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.

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.

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 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.

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

This study uses Computational Fluid Dynamics (CFD) to predict, analyze and validate the deposition patterns in a human lung for a Budesonide drug delivered from the Novolizer Dry Powder Inhaler device. We used a test case of known deposition patterns to validate our computational Euler Lagrangian-based deposition predictions. Two different lung models are used: (i) a basic ring-less trachea model and (ii) an advanced Human Zygote5 model. Unlike earlier attempts, the current simulations do not include the device in the computational domain. This greatly reduces the computational effort. To mimic the device, we model the inlet particle jet stream from the device as a spray entering the mouth in a conical fashion. Deposition studies in the various lung regions were performed. We were able to computationally predict and then demonstrate the enhanced deposition in the tracheal and first generation rings/ridges. The enhanced vorticity creation due to the ring structure and the geometrical design contributes to larger deposition in the Zygote5 model. These are in accord with existing data, unlike the ring-less model. Our validated results indicate the need to (i) introduce the ridges in the experimental casts and the CFD surface meshes to be anatomically consistent and obtain physiologically consistent depositions; (ii) introduce a factor to account for the recirculating lighter particles in empirical models.

A quasi-3D wire approach to model pulmonary airflow in human airways.

The models used for modeling the airflow in the human airways are either 0-dimensional compartmental or full 3-dimensional (3D) computational fluid dynamics (CFD) models. In the former, airways are treated as compartments, and the computations are performed with several assumptions, thereby generating a low-fidelity solution. The CFD method displays extremely high fidelity since the solution is obtained by solving the conservation equations in a physiologically consistent geometry. However, CFD models (1) require millions of degrees of freedom to accurately describe the geometry and to reduce the discretization errors, (2) have convergence problems, and (3) require several days to simulate a few breathing cycles. In this paper, we present a novel, fast-running, and robust quasi-3D wire model for modeling the airflow in the human lung airway. The wire mesh is obtained by contracting the high-fidelity lung airway surface mesh to a system of connected wires, with well-defined radii. The conservation equations are then solved in each wire. These wire meshes have around O(1000) degrees of freedom and hence are 3000 to 25 000 times faster than their CFD counterparts. The 3D spatial nature is also preserved since these wires are contracted out of the actual lung STL surface. The pressure readings between the 2 approaches showed minor difference (maximum error = 15%). In general, this formulation is fast and robust, allows geometric changes, and delivers high-fidelity solutions. Hence, this approach has great potential for more complicated problems including modeling of constricted/diseased lung sections and for calibrating the lung flow resistances through parameter inversion.

Particle transport in the human respiratory tract: formulation of a nodal inverse distance weighted Eulerian-Lagrangian transport and implementation of the Wind-Kessel algorithm for an oral delivery.

This paper is the first in a series wherein efficient computational methods are developed and implemented to accurately quantify the transport, deposition, and clearance of the microsized particles (range of interest: 2 to 10 µm) in the human respiratory tract. In particular, this paper (part I) deals with (i) development of a detailed 3D computational finite volume mesh comprising of the NOPL (nasal, oral, pharyngeal and larynx), trachea and several airway generations; (ii) use of CFD Research Corporation's finite volume Computational Biology (CoBi) flow solver to obtain the flow physics for an oral inhalation simulation; (iii) implement a novel and accurate nodal inverse distance weighted Eulerian-Lagrangian formulation to accurately obtain the deposition, and (iv) development of Wind-Kessel boundary condition algorithm. This new Wind-Kessel boundary condition algorithm allows the 'escaped' particles to reenter the airway through the outlets, thereby to an extent accounting for the drawbacks of having a finite number of lung generations in the computational mesh. The deposition rates in the NOPL, trachea, the first and second bifurcation were computed, and they were in reasonable accord with the Typical Path Length model. The quantitatively validated results indicate that these developments will be useful for (i) obtaining depositions in diseased lungs (because of asthma and COPD), for which there are no empirical models, and (ii) obtaining the secondary clearance (mucociliary clearance) of the deposited particles. Copyright © 2015 John Wiley & Sons, Ltd.