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A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases
Advanced Powder Technology xxx (xxxx) xxx
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Perspective article
A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases Kazunori Kadota a, Tomasz R. Sosnowski b, Satoshi Tobita c, Isao Tachibana c, Jun Yee Tse a, Hiromasa Uchiyama a, Yuichi Tozuka a,⇑ a b c
Osaka University of Pharmaceutical Sciences, 4-20-1 Nasahara, Takatsuki, Osaka 569-1094, Japan Warsaw University of Technology, Faculty of Chemical and Process Engineering, Warynskiego 1, 00-645 Warsaw, Poland Nippon Life Hospital, 2-1-54 Enokojima, Nishi-ku, Osaka-shi 550-0006, Japan
a r t i c l e
i n f o
Article history: Received 26 July 2019 Received in revised form 7 October 2019 Accepted 11 October 2019 Available online xxxx Keywords: Aerodynamic particle size Computational fluid dynamics Computed tomography Design of experiment Dry-powder inhaler
a b s t r a c t Compared with oral and parenteral formulations, inhaled formulations are attractive because of their great benefit and potential to enhance therapeutic effects of medications. Among the available inhaled formulations, powders used with dry-powder inhalers (DPIs) have become a preferred option because of their many advantages over other inhaled formulations. Additionally, a powder technological approach is required and available for sophisticated design of DPI formulations. To provide appropriate treatment using a DPI formulation, inhaled particles containing drugs should be delivered to the appropriate sites in the lungs of individual patients. It is indispensable that the design of DPI formulations specify particle properties suitable for a specific disease and the appropriate positions in the lungs to which the inhaled particles must be delivered. This article focuses on the current particle technological approach toward designing DPI formulations and numerical simulation analysis of behavior and deposition of inhaled particles in the lungs. As a future perspective from the viewpoint of pharmaceutical particle technology, a combination of experimental and simulation approaches is expected to improve the ability to obtain maximum lung delivery as well as target the site of deposition in the lungs of individual patients. Ó 2019 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.
1. Introduction The use of pulmonary drug delivery to treat lung diseases is rapidly expanding because pulmonary administration may have greater potential to enhance a drug’s therapeutic effect than that of oral and parenteral administration [1]. Rapid expansion and development in pulmonary drug delivery are expected because of the need for local treatments of the respiratory tract and systemic diseases [2,3]. The lungs are an ideal target for both respiratory diseases and systemic diseases. Generally, pulmonary delivery formulations enable higher dose, show rapid onset of the therapeutic effect, and avoid first-pass metabolism [4,5]. For respiratory diseases, inhalable formulations can reduce systemic side effects and achieve topical delivery with a high drug concentration [4,5]. Also, for systemic diseases, inhalable formulation can improve the drug absorption as the lungs have a large inner surface area of approximately 50–100 m2, a thin absorption barrier, and low enzymatic metabolic activity [6,7]. ⇑ Corresponding author. E-mail address: [email protected] (Y. Tozuka).
Inhalation drug delivery systems can be mainly divided into three categories: nebulizers, metered-dose inhalers, and drypowder inhalers (DPIs). Pros and cons of the three systems are summarized in Table 1. Among these available devices, DPIs have been widely accepted as a recommended drug delivery system because they offer ease of use, more convenient portability, and lower costs than other systems [8]. As further advantages, DPI formulations (i.e., drug in the form of powder inside the device) are preferred from the viewpoint of stability and processability. Particle technological approaches are very important for development and design of high-performance DPI formulations. The main factors responsible for good performance of DPIs are the size distribution of powder grains, their easy fluidization and aerosolization, and the reproducibility of the delivered dose. Although it is apparent that the design of the drug delivery device greatly contributes to its performance [9], it is not very easy to design the right inhalation system or to improve it. The effectiveness of DPI formulations for delivery into lungs also depends on the inhalation procedure or skill of the individual patients [10,11], and it would be difficult to control these factors for individual patients. Several researchers have stated that particle technology might be a useful approach to
https://doi.org/10.1016/j.apt.2019.10.013 0921-8831/Ó 2019 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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Table 1 The pros and cons of nebulizer, metered-dose inhaler, and dry-powder inhaler. Nebulizer Pros
Metered-dose inhaler Cons
Ease of use Absence of propellants Application for very high dose drug
Weak portability Slow administration High costs Maintenance and cleaning required
Pros Portability Quick administration
Dry-powder inhaler Cons
Pros
Difficulty of use Presence of propellants Occurrence of static electrical charge on the inner wall
controlling particle properties, which are strongly related to the performance of DPIs. The performance of a DPI formulation depends on various particle properties because the arrival position of inhaled particles is governed mainly by the aerodynamic size of aerosolized powder particles [12]. Particles with a diameter greater than 5 lm have a greater chance to deposit in the throat while particles with a diameter smaller than 0.5 lm may fail to deposit due to the influence of air molecules [4]. Thus, to effectively deliver inhaled particles deep into the lung, the aerodynamic particle size of inhaled particles must be within a suitable range (0.5–5 lm). Regarding the appropriate particle diameter for regional deposition, it is believed that extrafines (Dae < 3 lm) are more appropriate for lung periphery (i.e., alveolar) drug delivery, while particles 3–5 lm are expected to deposit more in the central part bronchial tree. Here the aerodynamic particle size is expressed according to the following equation:
sffiffiffiffiffiffiffiffi Dae ¼ D
qp q0 x
ð1Þ
where Dae is the aerodynamic particle size, D is the geometric particle size, qp and q0 are the densities of the particles and water (1 g/ cm3), respectively, and x is the dynamic shape factor [13,14]. Not only minimization of particle size but also variations in their morphology, such as the shape and surface structure of particles, in DPI formulations are important to improve the performance of drug delivery to lungs. Accordingly, particles with different aerodynamic diameters can be delivered and deposited in different sites in the lungs [15,16], and ultimately the physical and chemical properties of inhaled particles may affect their influence on lung physiology [17,18]. To enhance the therapeutic effect of a DPI formulation in individual patients, a design of inhaled powders with desirable particle properties required for delivery to the appropriate sites depends on the individual lung disease. Another concern about the development of inhaled formulations is the ability to accurately identify to which positions in lungs the inhaled particles should be delivered. In general, in vitro evaluation of the reachability of inhaled particles has been performed by using an Anderson Cascade Impactor (ACI) or Next Generation Impactor (NGI). These devices enable determination of the aerodynamic size distribution of aerosol particles released from an inhaler at operating conditions relevant to flows produced by an inhaling patient. However, there has been a lack of clarity about the accuracy of predictions of which parts of the airway the inhaled particles are deposited in regardless of in vitro measurements of ACI or NGI because real human lungs are quite complex geometric structures and show differences among individual persons [19,20]. Accurate analyses of the behavior and deposition of inhaled particles in the lungs are indispensable for delivering the DPI formulation to desirable sites in lungs, and can help enhance the therapeutic effects of DPI formulations in individual patients. To
Portability Ease of use Quick administration Absence of propellants Low costs Good stability and processability Flow-dependency
Cons Occurrence of static electrical charge on the inner wall Clumping of powders due to moisture
address these concerns, research using numerical simulations has been conducted to investigate the aerodynamic behavior and deposition of inhaled particles in the airways [21–25]. Especially, computational fluid dynamics (CFD) has been used to calculate the transport and deposition of particles in the respiratory system [26,27]. Furthermore, recent advances in discrete element method (DEM) modeling can be applied to the development for DPI formulations [28,29]. A combined CFD and DEM approach could be utilized to evaluate the performance of DPI formulations and devices [30]. In addition, rapid advancements in magnetic resonance imaging (MRI) scans and computed tomography (CT) can be used for representing the geometry of a specific respiratory system [31,32]. The real human respiratory system has a quite complicated geometry and variable dimensions that can be accurately modeled with these medical images [33]. The advancements of several simulations and medical imaging techniques could lead to the development of individualized medicine for lung disease, delivered by pulmonary administration. The intent of this perspective article is to describe the factors of pharmaceutical particle technology known to contribute to the individual design of DPI formulations toward personalized medicine in respiratory disease. In the next section, the main particle engineering for design of DPI formulations with various particle properties is described. Another section introduces several numerical simulations, including CFD and DEM, for obtaining accurate knowledge and making predictions of the positions in lungs to which inhaled particles are delivered. The combination of experimental and simulation approaches is expected to improve the chances of maximizing lung delivery of drug particles and targeting the best sites of deposition in the lungs of individual patients, which potentially would enhance the therapeutic effect of aerosol DPI formulation therapy. 2. Particle engineering for dry-powder inhaler formulations 2.1. Milling The design and development of desirable DPI formulations for individual patients can be achieved by particle engineering. The traditional way of producing fine particles for DPI formulations is milling, which is a top-down method [34,35]. Milling is typically used for breaking drug crystals into fine particles, but control of particle shape and morphology is limited by this process. Distinct from milling, spray drying techniques such as conventional spray drying and spray-freeze drying enable the preparation of particles with desirable shapes by forming instead of breaking. 2.2. Spray drying Spray drying is commonly and conventionally used for preparing DPI formulations as an alternative method [36,37]. Compared
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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with the milling process, spray drying allows flexible control of the particle properties (size, shape, morphology, surface characteristics) [38]. Spray drying can be varied by adjusting various solution properties, such as solvent composition, solute concentration, viscosity, and surface tension of the precursor solution [39]; additionally, it can be used to manipulate various process parameters, including nozzle properties, such as the feed rate of liquids/gas, drying temperature, and drying rate [40]. Control of these factors, including solution properties and process parameters for spray drying, can generate particles with the appropriate properties for DPI formulations [41,42]. The main aim of aerosolizing powders by using spray drying is to achieve an ideal aerodynamic particle size and a narrow particle size distribution. Rifampicin is used for the treatment of tuberculosis, and the delivery of this drug directly to the pulmonary alveoli in the respiratory system is anticipated [43,44] because tuberculosis is known to infect alveolar macrophages and affect the pathogenesis of this disease [45]. Therefore, development of DPI formulations, including those using a drug for treatment and prevention of tuberculosis, would be required to deliver the drug to deeper lungs locations, such as the alveoli. We previously succeeded in preparing a porous powder containing rifampicin and dextran to deliver these particles into deeper lung positions [46,47]. By applying the Péclet number, design of DPI formulations processed by spray drying can introduce hollow low-density particles with controlled surface morphology and particles with functional layers [48–50]. The Péclet number is a useful particle formation parameter to be considered in spray drying, and it is closely related to the ratio of the solvent evaporation rate and solute diffusion rate [51].
clet number ¼ Pe
r2
s Di
ð2Þ
where r denotes the droplet radius, Di is the diffusion coefficient of solute i in the liquid phase, and s is the drying time. A smaller Péclet number indicates that the morphology could form a solid structure with homogeneous components distributed within the particles, whereas a larger Péclet number indicates a morphology of particles with hollow or wrinkled structures [39]. If we can prepare and design DPI formulation by manipulating the Péclet number freely, the desirable DPI formulation for an individual patient might be achieved by particle engineering. It also has been demonstrated that more sophisticated control over particle structure can be obtained by controlling the drying and evaporation rates, especially if powders are formed from nanocolloidal suspensions [52]. Recently a Design of Experiment (DoE) approach has been employed to systematically optimize and identify the critical factors of DPI spray-dried formulations because DoE is a rational experimental tool [53–55]. However, the currently approved excipients for pulmonary formulations have been restricted to a few sugars, hydrophobic additives, and lipids that naturally occur in the lungs and are used in surfactants from the viewpoint of safety [56,57]. DoE can provide a structural statistical system that mathematically connects process parameters with the results of output parameters, which helps to identify the critical material attributes and critical process parameters for DPI spray-dried formulations [58,59]. By applying the DoE approach to the design of DPI spray-dried formulations, we can expand the possibilities of development of DPI formulations, including a specific drug and limited excipients, with an ideal aerodynamic particle size range and a narrow distribution. An appropriate DoE that uses response surface methodology (RSM) is effective for the optimization process. We sought to develop an optimized spray drying process parameter for the preparation of DPI formulations, including levofloxacin by RSM. A three-level and three-factor central composite face-centered
3
design was used to develop desirable formulations for DPI. Inlet gas temperature, flow rate, and liquid precursor feed rate were chosen as the factor variables expected to have major contributions, as shown also by several other studies that adopted the optimization of these three parameters [60–62]. The response variables evaluated were the aerodynamic properties (emitted dose: ED, fine particle fraction: FPF, extra-fine particle fraction: eFPF) and the yield percentage of the dry powders. UnscramblerÒ X 10.1 software (CAMO software Japan, Tokyo, Japan) was used for the entire DoE project. After collection of data from 17 assigned spray drying runs, a set of data evaluation reports based on a mathematical model was generated. The following second-order polynomial equation corresponds to the data:
Y ¼ b0 þ b1 X 1 þ b2 X 2 þ b3 X 3 þ b1;1 X 12 þ b2;2 X 22 þ b3;3 X 32 þ b12 X 1 X 2 þ b1;3 X 1 X 3 þ b2;3 X 2 X 3
ð3Þ
where Y is the response variable, Xn represents the factor variables, b0 is the value at the center point (0,0,0) of the DoE, bn (n–0) are the regression coefficients computed from the experimental values of Y, X2n denotes the quadratic terms and XaXb (a and b = 1, 2, and 3) represent the interaction terms. Fig. 1 shows an example of the usefulness of DoE in product optimization. A three-dimensional response surface plot (Fig. 1a) showed the specific influence of two factors on a single response parameter. The horizontal axes are the degrees of two particular factor variables, while factors other than these two must be fixed at a certain value. In this case, the inlet gas temperature of spray drying was fixed, and the effects of the feed rate and gas flow temperature on the FPF of the products are revealed. The color intensity indicates the range of the vertical axis; e.g., high-FPF values are marked as red. Fig. 1b is a contour plot generated by the same data from Fig. 1a but in two dimensions. The oval in the plot represents the target level, whereas the arrow indicates the location of desired parameters [63]. Each response variable can be revealed individually. Including the target level of FPF shown in Fig. 1b, Fig. 1c shows the design space combined by the target levels of all response variables. If the output is anticipated for a specific use, for example, to meet the requirement of deeper lung delivery for an anti-tuberculosis effect, the target level could be adjusted and the corresponding parameter range would change. Moreover, to produce a product that can meet requirements in multiple aspects, the RSM is also able to identify suitable parameter ranges [64]. Given that four responsible variables, i.e., ED, FPF, eFPF, and yield percentage, were adopted in the present DoE approach, a single design space region can attain a maximum of four target levels simultaneously, which is marked in green. Indeed, the collection of data for validation runs is crucial to ensure the reliability of the design space plot. The responses of the validation runs are a proper quantitative indicator to evaluate whether the suggestions from the design plot are credible [63]. Identifying the critical factors affecting the response variable is also a purpose of adopting DoE analysis. From Eq. (3), the regression coefficient represents the effect of factors on responses. Also, by applying analysis of variance to the model, the significance of the factors or the interactions could be demonstrated quantitatively. Critical factors that contributed to each response variable can be identified [65]. The findings can be useful for enhancement of particle engineering technology. 2.3. Spray-freeze drying and innovative method Spray-freeze drying is attractive as a relatively new drying process that combines spray drying and freeze drying to produce DPI formulations [66,67]. In this process, atomized droplets from spray are rapidly frozen in a vessel containing a cryogenic substance,
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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(a)
(b)
(c)
Fig. 1. (a) A 3D response surface showing the influence of feed rate and gas flow rate on the fine particle fraction. (b) A 2D contour plot of (a) showing the region of the targeted fine particle fraction value range. (c) A predicted design space combining all response target levels. The inlet gas temperature was fixed in all plots.
such as liquid nitrogen. Sublimation of ice from the frozen droplets results in particles with porous structures and low density that are appropriate for DPI formulations. Although there are several issues, such as the limitations of the drugs and cost for practical use, further development for producing DPI formulations is expected. Inkjet printing has emerged as a relevant technique for producing DPI formulations because this process can provide narrow particle size distribution and control over particle morphology and dosage volume [68]. López-Iglesias et al. [69] reported that particles obtained by the inkjet printing technique could be applicable for the treatment of several pulmonary diseases, such as asthma, chronic obstructive pulmonary disease (COPD), or cystic fibrosis. This process also can be extended to personalized medicine by using DPI formulations.
3. Analysis and prediction of behavior and deposition of DPI formulations in airways Several multiphase CFD simulations make it possible to predict and calculate the particle behavior in the respiratory system [70,71]. Usually, the effects of particle behavior on the flow field and interactions between particles can be ignored assuming a dilute phase of inhaled particles in the airways [72,73]. Kleinstreuer et al. [70] investigated the gravitational effect on microparticle deposition and indicated that the particle sedimentation may change deposition patterns in human airways, especially under slow-inhalation conditions. We previously reported that CFD coupled with a discrete phase model succeeded in calculating the particle behavior and deposition in airways [74,75]. Thus, a multiphase CFD technique can contribute to the prediction and analysis of particles in DPI formulations in airways. Combined CFD and DEM approaches will be useful for further advanced research on delivering particles in DPI formulations to appropriate lung positions of individual patients [25]. Recently, accurate deposition was calculated by performing the combined DEM and CFD simulations with a simple branched lung model, and the obtained simulation results showed better agreement with the experimental data than with the data obtained by CFD only [76]. Furthermore, the results of numerical modeling of spherical particle transport and deposition in the pulmonary airways were accurately evaluated by using CFD coupled with DEM by Chen et al. [77]. Therefore, numerical simulation combining CFD and DEM can contribute to advances in the development of DPI formulations [78].
For accurate analysis of particle behavior and deposition in the airways of individual patients, it is beneficial to use more realistic human airway models. MRI and CT scans have been performed to reconstruct the real human airway geometry [79,80] after importing medical scans into image processing software. Zhang et al. [34] calculated the particle behavior and deposition in human airways with complicated cross sections by accurately modeling involving such medical images. Rahimi-Gorji et al. [81] also calculated airflow behavior and particle transport and deposition in a realistic model of human airways in different breathing conditions. Thus, recent progress in medical technologies, such as in CT and MRI, will enable us to create a geometrical model of an individual patient’s respiratory system [82]. We have performed the analysis and prediction of inhaled particles in a realistic human model suffering from a COPD to assess application of personalized medicine using a DPI formulation. Here, we present examples of the procedure for analyzing and predicting the behavior and deposition of inhaled particles in the realistic airway models of each patient. Fig. 2 shows a flow chart of the procedure starting from creating realistic human airway models to analyzing the behavior and deposition of inhaled particles. An overview of the steps involved in medical image processing and analysis using CFD simulation for patients in a three-dimensional airway model is presented. Fig. 3 shows axial and coronal views of CT data images imported into Materialise’s Interactive Medical Image Control System (Mimics) medical processing software. Segmentation of airways from CT images of several organs was performed by applying various image processing operations using a medical processing tool for visualization, CT image segmentation, and calculation of threedimensional models. Individualized airway models for calculations were used to create these CT images (Fig. 3(c)). Fig. 4 shows the difference in airflow rate distribution between two patients: (1) an 82-year-old male patient with COPD and (2) a 69-year-old male patient with COPD. The airflow velocities in the airways of the individual patients were different because of the differences between the created airway models for the individual patients. Another issue that should be considered in personalized drug delivery of DPI formulations is the variability of inhalation flow dynamics and the peak inspiratory flow rate (PIFR) among different patients that is caused by using a particular inhaler. These relationships have been studied by several investigators [83–85] and have shown that there is a notable variability of aerosol flow rates obtained in various DPIs by patients with different ages,
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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particles (i.e., FPF and eFPF) has been found to depend on the flow achieved with a given DPI by a given patient [87–89]. All of these findings indicate that the behavior of inhaled powders with the same particle properties could vary among patients, which would cause variability in the deposited site and availability of an aerosolized drug in the airways of individual patients. By applying the proposed approach to predict the deposited site and reachability of inhaled particles in the airways of individual patients, we can expand the possibilities of desirable development and design of DPI formulations, including for specific drugs and specific patients. The present research can be further extended to the analysis of the airflow and particle behavior of inhaled particles through realistic human airways, which can be useful for pharmaceutical companies or physicians to decide on the proper therapeutic procedure for individual patients.
Acquisition of CT images
Creation of computerized 3D images
Conversion from CT images to calculated model
4. Conclusions and remarks
Modification of airway models to calculate
Analysis of airflow and behavior of particles Fig. 2. Flow chart of the procedure starting from creating the human airways model to analyzing the particle behavior.
sexes, and health condition. Changes in flow intensity in different patients using inhalers can be modeled by using a CFD approach. It is worth noting that when high PIFRs are obtained in DPIs characterized by low internal resistance, the inertial deposition (impaction) of inhaled drug particles in the throat is intensified, which reduces their penetration into more distal positions in the lungs [86–88]. A degree of dispersion of powder formulation into fine
(a)
(b)
The use of spray drying in the design and development of DPI formulations has remained popular and is used more often than other methods. To provide individual patients with appropriate and personalized inhaled formulations, a DoE that specifies the use of spray drying is an efficient and potentially useful approach because it can optimize parameters limited to the excipients for individual formulations. When spray-freeze dying or threedimensional printing technologies become versatile and applicable, a DoE approach to further develop these technologies may be more effective in the development of DPI formulations for individual patients. Furthermore, combinational techniques of numerical simulations, including CFD and DEM, and medical imaging approaches, including CT and MRI, are more important for recognizing the above-mentioned problem. Numerical simulations using both CFD and DEM can provide the visualization and prediction of particle flow and deposition in airways. After addition of the detailed geometry of the respiratory system and inhalation patterns of individual patients to the numerical simulations, the development and design of personalized formulations for pulmonary delivery might be accomplished. Such an achievement has the potential to reduce side effects and improve medication compliance by patients. Regarding the future of pharmaceutical particle technology, the combination of experimental and simulation approaches is expected to improve the ability to obtain the maximum lung delivery and target the site of deposition in the lungs of individual patients.
(c)
Fig. 3. (a) CT axial view of lungs; (b) CT coronal view of lungs; (c) Human airways model created from CT images.
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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(a-1)
(b-1)
(a-2)
(b-2)
Fig. 4. (a) Velocity streamlines. (b) Deposited particles in each human airway. (1) An 82-year-old male patient with COPD; (2) A 69-year-old male patient with COPD.
Declaration of Competing Interest The authors report no declaration of interest. Acknowledgements The authors thank Hitachi Automotive Systems Measurement, Ltd, Japan for providing the Jethaler. We appreciate Siemens PLM Software Computational Dynamics K.K. and Materialise Japan for supporting the analysis of CFD and the creation of the airway model, respectively. We also thank Dr. Munehiro Maeda and Dr. Daisuke Maki in Nippon Life Hospital for helping us to take the
medical radiographical images in the form of computed tomographic data. T.R.S. acknowledges the support from NCN (Poland), Poland under the project No. 2018/29/B/ST8/00273.
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Perspective article
A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases Kazunori Kadota a, Tomasz R. Sosnowski b, Satoshi Tobita c, Isao Tachibana c, Jun Yee Tse a, Hiromasa Uchiyama a, Yuichi Tozuka a,⇑ a b c
Osaka University of Pharmaceutical Sciences, 4-20-1 Nasahara, Takatsuki, Osaka 569-1094, Japan Warsaw University of Technology, Faculty of Chemical and Process Engineering, Warynskiego 1, 00-645 Warsaw, Poland Nippon Life Hospital, 2-1-54 Enokojima, Nishi-ku, Osaka-shi 550-0006, Japan
a r t i c l e
i n f o
Article history: Received 26 July 2019 Received in revised form 7 October 2019 Accepted 11 October 2019 Available online xxxx Keywords: Aerodynamic particle size Computational fluid dynamics Computed tomography Design of experiment Dry-powder inhaler
a b s t r a c t Compared with oral and parenteral formulations, inhaled formulations are attractive because of their great benefit and potential to enhance therapeutic effects of medications. Among the available inhaled formulations, powders used with dry-powder inhalers (DPIs) have become a preferred option because of their many advantages over other inhaled formulations. Additionally, a powder technological approach is required and available for sophisticated design of DPI formulations. To provide appropriate treatment using a DPI formulation, inhaled particles containing drugs should be delivered to the appropriate sites in the lungs of individual patients. It is indispensable that the design of DPI formulations specify particle properties suitable for a specific disease and the appropriate positions in the lungs to which the inhaled particles must be delivered. This article focuses on the current particle technological approach toward designing DPI formulations and numerical simulation analysis of behavior and deposition of inhaled particles in the lungs. As a future perspective from the viewpoint of pharmaceutical particle technology, a combination of experimental and simulation approaches is expected to improve the ability to obtain maximum lung delivery as well as target the site of deposition in the lungs of individual patients. Ó 2019 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.
1. Introduction The use of pulmonary drug delivery to treat lung diseases is rapidly expanding because pulmonary administration may have greater potential to enhance a drug’s therapeutic effect than that of oral and parenteral administration [1]. Rapid expansion and development in pulmonary drug delivery are expected because of the need for local treatments of the respiratory tract and systemic diseases [2,3]. The lungs are an ideal target for both respiratory diseases and systemic diseases. Generally, pulmonary delivery formulations enable higher dose, show rapid onset of the therapeutic effect, and avoid first-pass metabolism [4,5]. For respiratory diseases, inhalable formulations can reduce systemic side effects and achieve topical delivery with a high drug concentration [4,5]. Also, for systemic diseases, inhalable formulation can improve the drug absorption as the lungs have a large inner surface area of approximately 50–100 m2, a thin absorption barrier, and low enzymatic metabolic activity [6,7]. ⇑ Corresponding author. E-mail address: [email protected] (Y. Tozuka).
Inhalation drug delivery systems can be mainly divided into three categories: nebulizers, metered-dose inhalers, and drypowder inhalers (DPIs). Pros and cons of the three systems are summarized in Table 1. Among these available devices, DPIs have been widely accepted as a recommended drug delivery system because they offer ease of use, more convenient portability, and lower costs than other systems [8]. As further advantages, DPI formulations (i.e., drug in the form of powder inside the device) are preferred from the viewpoint of stability and processability. Particle technological approaches are very important for development and design of high-performance DPI formulations. The main factors responsible for good performance of DPIs are the size distribution of powder grains, their easy fluidization and aerosolization, and the reproducibility of the delivered dose. Although it is apparent that the design of the drug delivery device greatly contributes to its performance [9], it is not very easy to design the right inhalation system or to improve it. The effectiveness of DPI formulations for delivery into lungs also depends on the inhalation procedure or skill of the individual patients [10,11], and it would be difficult to control these factors for individual patients. Several researchers have stated that particle technology might be a useful approach to
https://doi.org/10.1016/j.apt.2019.10.013 0921-8831/Ó 2019 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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Table 1 The pros and cons of nebulizer, metered-dose inhaler, and dry-powder inhaler. Nebulizer Pros
Metered-dose inhaler Cons
Ease of use Absence of propellants Application for very high dose drug
Weak portability Slow administration High costs Maintenance and cleaning required
Pros Portability Quick administration
Dry-powder inhaler Cons
Pros
Difficulty of use Presence of propellants Occurrence of static electrical charge on the inner wall
controlling particle properties, which are strongly related to the performance of DPIs. The performance of a DPI formulation depends on various particle properties because the arrival position of inhaled particles is governed mainly by the aerodynamic size of aerosolized powder particles [12]. Particles with a diameter greater than 5 lm have a greater chance to deposit in the throat while particles with a diameter smaller than 0.5 lm may fail to deposit due to the influence of air molecules [4]. Thus, to effectively deliver inhaled particles deep into the lung, the aerodynamic particle size of inhaled particles must be within a suitable range (0.5–5 lm). Regarding the appropriate particle diameter for regional deposition, it is believed that extrafines (Dae < 3 lm) are more appropriate for lung periphery (i.e., alveolar) drug delivery, while particles 3–5 lm are expected to deposit more in the central part bronchial tree. Here the aerodynamic particle size is expressed according to the following equation:
sffiffiffiffiffiffiffiffi Dae ¼ D
qp q0 x
ð1Þ
where Dae is the aerodynamic particle size, D is the geometric particle size, qp and q0 are the densities of the particles and water (1 g/ cm3), respectively, and x is the dynamic shape factor [13,14]. Not only minimization of particle size but also variations in their morphology, such as the shape and surface structure of particles, in DPI formulations are important to improve the performance of drug delivery to lungs. Accordingly, particles with different aerodynamic diameters can be delivered and deposited in different sites in the lungs [15,16], and ultimately the physical and chemical properties of inhaled particles may affect their influence on lung physiology [17,18]. To enhance the therapeutic effect of a DPI formulation in individual patients, a design of inhaled powders with desirable particle properties required for delivery to the appropriate sites depends on the individual lung disease. Another concern about the development of inhaled formulations is the ability to accurately identify to which positions in lungs the inhaled particles should be delivered. In general, in vitro evaluation of the reachability of inhaled particles has been performed by using an Anderson Cascade Impactor (ACI) or Next Generation Impactor (NGI). These devices enable determination of the aerodynamic size distribution of aerosol particles released from an inhaler at operating conditions relevant to flows produced by an inhaling patient. However, there has been a lack of clarity about the accuracy of predictions of which parts of the airway the inhaled particles are deposited in regardless of in vitro measurements of ACI or NGI because real human lungs are quite complex geometric structures and show differences among individual persons [19,20]. Accurate analyses of the behavior and deposition of inhaled particles in the lungs are indispensable for delivering the DPI formulation to desirable sites in lungs, and can help enhance the therapeutic effects of DPI formulations in individual patients. To
Portability Ease of use Quick administration Absence of propellants Low costs Good stability and processability Flow-dependency
Cons Occurrence of static electrical charge on the inner wall Clumping of powders due to moisture
address these concerns, research using numerical simulations has been conducted to investigate the aerodynamic behavior and deposition of inhaled particles in the airways [21–25]. Especially, computational fluid dynamics (CFD) has been used to calculate the transport and deposition of particles in the respiratory system [26,27]. Furthermore, recent advances in discrete element method (DEM) modeling can be applied to the development for DPI formulations [28,29]. A combined CFD and DEM approach could be utilized to evaluate the performance of DPI formulations and devices [30]. In addition, rapid advancements in magnetic resonance imaging (MRI) scans and computed tomography (CT) can be used for representing the geometry of a specific respiratory system [31,32]. The real human respiratory system has a quite complicated geometry and variable dimensions that can be accurately modeled with these medical images [33]. The advancements of several simulations and medical imaging techniques could lead to the development of individualized medicine for lung disease, delivered by pulmonary administration. The intent of this perspective article is to describe the factors of pharmaceutical particle technology known to contribute to the individual design of DPI formulations toward personalized medicine in respiratory disease. In the next section, the main particle engineering for design of DPI formulations with various particle properties is described. Another section introduces several numerical simulations, including CFD and DEM, for obtaining accurate knowledge and making predictions of the positions in lungs to which inhaled particles are delivered. The combination of experimental and simulation approaches is expected to improve the chances of maximizing lung delivery of drug particles and targeting the best sites of deposition in the lungs of individual patients, which potentially would enhance the therapeutic effect of aerosol DPI formulation therapy. 2. Particle engineering for dry-powder inhaler formulations 2.1. Milling The design and development of desirable DPI formulations for individual patients can be achieved by particle engineering. The traditional way of producing fine particles for DPI formulations is milling, which is a top-down method [34,35]. Milling is typically used for breaking drug crystals into fine particles, but control of particle shape and morphology is limited by this process. Distinct from milling, spray drying techniques such as conventional spray drying and spray-freeze drying enable the preparation of particles with desirable shapes by forming instead of breaking. 2.2. Spray drying Spray drying is commonly and conventionally used for preparing DPI formulations as an alternative method [36,37]. Compared
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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with the milling process, spray drying allows flexible control of the particle properties (size, shape, morphology, surface characteristics) [38]. Spray drying can be varied by adjusting various solution properties, such as solvent composition, solute concentration, viscosity, and surface tension of the precursor solution [39]; additionally, it can be used to manipulate various process parameters, including nozzle properties, such as the feed rate of liquids/gas, drying temperature, and drying rate [40]. Control of these factors, including solution properties and process parameters for spray drying, can generate particles with the appropriate properties for DPI formulations [41,42]. The main aim of aerosolizing powders by using spray drying is to achieve an ideal aerodynamic particle size and a narrow particle size distribution. Rifampicin is used for the treatment of tuberculosis, and the delivery of this drug directly to the pulmonary alveoli in the respiratory system is anticipated [43,44] because tuberculosis is known to infect alveolar macrophages and affect the pathogenesis of this disease [45]. Therefore, development of DPI formulations, including those using a drug for treatment and prevention of tuberculosis, would be required to deliver the drug to deeper lungs locations, such as the alveoli. We previously succeeded in preparing a porous powder containing rifampicin and dextran to deliver these particles into deeper lung positions [46,47]. By applying the Péclet number, design of DPI formulations processed by spray drying can introduce hollow low-density particles with controlled surface morphology and particles with functional layers [48–50]. The Péclet number is a useful particle formation parameter to be considered in spray drying, and it is closely related to the ratio of the solvent evaporation rate and solute diffusion rate [51].
clet number ¼ Pe
r2
s Di
ð2Þ
where r denotes the droplet radius, Di is the diffusion coefficient of solute i in the liquid phase, and s is the drying time. A smaller Péclet number indicates that the morphology could form a solid structure with homogeneous components distributed within the particles, whereas a larger Péclet number indicates a morphology of particles with hollow or wrinkled structures [39]. If we can prepare and design DPI formulation by manipulating the Péclet number freely, the desirable DPI formulation for an individual patient might be achieved by particle engineering. It also has been demonstrated that more sophisticated control over particle structure can be obtained by controlling the drying and evaporation rates, especially if powders are formed from nanocolloidal suspensions [52]. Recently a Design of Experiment (DoE) approach has been employed to systematically optimize and identify the critical factors of DPI spray-dried formulations because DoE is a rational experimental tool [53–55]. However, the currently approved excipients for pulmonary formulations have been restricted to a few sugars, hydrophobic additives, and lipids that naturally occur in the lungs and are used in surfactants from the viewpoint of safety [56,57]. DoE can provide a structural statistical system that mathematically connects process parameters with the results of output parameters, which helps to identify the critical material attributes and critical process parameters for DPI spray-dried formulations [58,59]. By applying the DoE approach to the design of DPI spray-dried formulations, we can expand the possibilities of development of DPI formulations, including a specific drug and limited excipients, with an ideal aerodynamic particle size range and a narrow distribution. An appropriate DoE that uses response surface methodology (RSM) is effective for the optimization process. We sought to develop an optimized spray drying process parameter for the preparation of DPI formulations, including levofloxacin by RSM. A three-level and three-factor central composite face-centered
3
design was used to develop desirable formulations for DPI. Inlet gas temperature, flow rate, and liquid precursor feed rate were chosen as the factor variables expected to have major contributions, as shown also by several other studies that adopted the optimization of these three parameters [60–62]. The response variables evaluated were the aerodynamic properties (emitted dose: ED, fine particle fraction: FPF, extra-fine particle fraction: eFPF) and the yield percentage of the dry powders. UnscramblerÒ X 10.1 software (CAMO software Japan, Tokyo, Japan) was used for the entire DoE project. After collection of data from 17 assigned spray drying runs, a set of data evaluation reports based on a mathematical model was generated. The following second-order polynomial equation corresponds to the data:
Y ¼ b0 þ b1 X 1 þ b2 X 2 þ b3 X 3 þ b1;1 X 12 þ b2;2 X 22 þ b3;3 X 32 þ b12 X 1 X 2 þ b1;3 X 1 X 3 þ b2;3 X 2 X 3
ð3Þ
where Y is the response variable, Xn represents the factor variables, b0 is the value at the center point (0,0,0) of the DoE, bn (n–0) are the regression coefficients computed from the experimental values of Y, X2n denotes the quadratic terms and XaXb (a and b = 1, 2, and 3) represent the interaction terms. Fig. 1 shows an example of the usefulness of DoE in product optimization. A three-dimensional response surface plot (Fig. 1a) showed the specific influence of two factors on a single response parameter. The horizontal axes are the degrees of two particular factor variables, while factors other than these two must be fixed at a certain value. In this case, the inlet gas temperature of spray drying was fixed, and the effects of the feed rate and gas flow temperature on the FPF of the products are revealed. The color intensity indicates the range of the vertical axis; e.g., high-FPF values are marked as red. Fig. 1b is a contour plot generated by the same data from Fig. 1a but in two dimensions. The oval in the plot represents the target level, whereas the arrow indicates the location of desired parameters [63]. Each response variable can be revealed individually. Including the target level of FPF shown in Fig. 1b, Fig. 1c shows the design space combined by the target levels of all response variables. If the output is anticipated for a specific use, for example, to meet the requirement of deeper lung delivery for an anti-tuberculosis effect, the target level could be adjusted and the corresponding parameter range would change. Moreover, to produce a product that can meet requirements in multiple aspects, the RSM is also able to identify suitable parameter ranges [64]. Given that four responsible variables, i.e., ED, FPF, eFPF, and yield percentage, were adopted in the present DoE approach, a single design space region can attain a maximum of four target levels simultaneously, which is marked in green. Indeed, the collection of data for validation runs is crucial to ensure the reliability of the design space plot. The responses of the validation runs are a proper quantitative indicator to evaluate whether the suggestions from the design plot are credible [63]. Identifying the critical factors affecting the response variable is also a purpose of adopting DoE analysis. From Eq. (3), the regression coefficient represents the effect of factors on responses. Also, by applying analysis of variance to the model, the significance of the factors or the interactions could be demonstrated quantitatively. Critical factors that contributed to each response variable can be identified [65]. The findings can be useful for enhancement of particle engineering technology. 2.3. Spray-freeze drying and innovative method Spray-freeze drying is attractive as a relatively new drying process that combines spray drying and freeze drying to produce DPI formulations [66,67]. In this process, atomized droplets from spray are rapidly frozen in a vessel containing a cryogenic substance,
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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(a)
(b)
(c)
Fig. 1. (a) A 3D response surface showing the influence of feed rate and gas flow rate on the fine particle fraction. (b) A 2D contour plot of (a) showing the region of the targeted fine particle fraction value range. (c) A predicted design space combining all response target levels. The inlet gas temperature was fixed in all plots.
such as liquid nitrogen. Sublimation of ice from the frozen droplets results in particles with porous structures and low density that are appropriate for DPI formulations. Although there are several issues, such as the limitations of the drugs and cost for practical use, further development for producing DPI formulations is expected. Inkjet printing has emerged as a relevant technique for producing DPI formulations because this process can provide narrow particle size distribution and control over particle morphology and dosage volume [68]. López-Iglesias et al. [69] reported that particles obtained by the inkjet printing technique could be applicable for the treatment of several pulmonary diseases, such as asthma, chronic obstructive pulmonary disease (COPD), or cystic fibrosis. This process also can be extended to personalized medicine by using DPI formulations.
3. Analysis and prediction of behavior and deposition of DPI formulations in airways Several multiphase CFD simulations make it possible to predict and calculate the particle behavior in the respiratory system [70,71]. Usually, the effects of particle behavior on the flow field and interactions between particles can be ignored assuming a dilute phase of inhaled particles in the airways [72,73]. Kleinstreuer et al. [70] investigated the gravitational effect on microparticle deposition and indicated that the particle sedimentation may change deposition patterns in human airways, especially under slow-inhalation conditions. We previously reported that CFD coupled with a discrete phase model succeeded in calculating the particle behavior and deposition in airways [74,75]. Thus, a multiphase CFD technique can contribute to the prediction and analysis of particles in DPI formulations in airways. Combined CFD and DEM approaches will be useful for further advanced research on delivering particles in DPI formulations to appropriate lung positions of individual patients [25]. Recently, accurate deposition was calculated by performing the combined DEM and CFD simulations with a simple branched lung model, and the obtained simulation results showed better agreement with the experimental data than with the data obtained by CFD only [76]. Furthermore, the results of numerical modeling of spherical particle transport and deposition in the pulmonary airways were accurately evaluated by using CFD coupled with DEM by Chen et al. [77]. Therefore, numerical simulation combining CFD and DEM can contribute to advances in the development of DPI formulations [78].
For accurate analysis of particle behavior and deposition in the airways of individual patients, it is beneficial to use more realistic human airway models. MRI and CT scans have been performed to reconstruct the real human airway geometry [79,80] after importing medical scans into image processing software. Zhang et al. [34] calculated the particle behavior and deposition in human airways with complicated cross sections by accurately modeling involving such medical images. Rahimi-Gorji et al. [81] also calculated airflow behavior and particle transport and deposition in a realistic model of human airways in different breathing conditions. Thus, recent progress in medical technologies, such as in CT and MRI, will enable us to create a geometrical model of an individual patient’s respiratory system [82]. We have performed the analysis and prediction of inhaled particles in a realistic human model suffering from a COPD to assess application of personalized medicine using a DPI formulation. Here, we present examples of the procedure for analyzing and predicting the behavior and deposition of inhaled particles in the realistic airway models of each patient. Fig. 2 shows a flow chart of the procedure starting from creating realistic human airway models to analyzing the behavior and deposition of inhaled particles. An overview of the steps involved in medical image processing and analysis using CFD simulation for patients in a three-dimensional airway model is presented. Fig. 3 shows axial and coronal views of CT data images imported into Materialise’s Interactive Medical Image Control System (Mimics) medical processing software. Segmentation of airways from CT images of several organs was performed by applying various image processing operations using a medical processing tool for visualization, CT image segmentation, and calculation of threedimensional models. Individualized airway models for calculations were used to create these CT images (Fig. 3(c)). Fig. 4 shows the difference in airflow rate distribution between two patients: (1) an 82-year-old male patient with COPD and (2) a 69-year-old male patient with COPD. The airflow velocities in the airways of the individual patients were different because of the differences between the created airway models for the individual patients. Another issue that should be considered in personalized drug delivery of DPI formulations is the variability of inhalation flow dynamics and the peak inspiratory flow rate (PIFR) among different patients that is caused by using a particular inhaler. These relationships have been studied by several investigators [83–85] and have shown that there is a notable variability of aerosol flow rates obtained in various DPIs by patients with different ages,
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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particles (i.e., FPF and eFPF) has been found to depend on the flow achieved with a given DPI by a given patient [87–89]. All of these findings indicate that the behavior of inhaled powders with the same particle properties could vary among patients, which would cause variability in the deposited site and availability of an aerosolized drug in the airways of individual patients. By applying the proposed approach to predict the deposited site and reachability of inhaled particles in the airways of individual patients, we can expand the possibilities of desirable development and design of DPI formulations, including for specific drugs and specific patients. The present research can be further extended to the analysis of the airflow and particle behavior of inhaled particles through realistic human airways, which can be useful for pharmaceutical companies or physicians to decide on the proper therapeutic procedure for individual patients.
Acquisition of CT images
Creation of computerized 3D images
Conversion from CT images to calculated model
4. Conclusions and remarks
Modification of airway models to calculate
Analysis of airflow and behavior of particles Fig. 2. Flow chart of the procedure starting from creating the human airways model to analyzing the particle behavior.
sexes, and health condition. Changes in flow intensity in different patients using inhalers can be modeled by using a CFD approach. It is worth noting that when high PIFRs are obtained in DPIs characterized by low internal resistance, the inertial deposition (impaction) of inhaled drug particles in the throat is intensified, which reduces their penetration into more distal positions in the lungs [86–88]. A degree of dispersion of powder formulation into fine
(a)
(b)
The use of spray drying in the design and development of DPI formulations has remained popular and is used more often than other methods. To provide individual patients with appropriate and personalized inhaled formulations, a DoE that specifies the use of spray drying is an efficient and potentially useful approach because it can optimize parameters limited to the excipients for individual formulations. When spray-freeze dying or threedimensional printing technologies become versatile and applicable, a DoE approach to further develop these technologies may be more effective in the development of DPI formulations for individual patients. Furthermore, combinational techniques of numerical simulations, including CFD and DEM, and medical imaging approaches, including CT and MRI, are more important for recognizing the above-mentioned problem. Numerical simulations using both CFD and DEM can provide the visualization and prediction of particle flow and deposition in airways. After addition of the detailed geometry of the respiratory system and inhalation patterns of individual patients to the numerical simulations, the development and design of personalized formulations for pulmonary delivery might be accomplished. Such an achievement has the potential to reduce side effects and improve medication compliance by patients. Regarding the future of pharmaceutical particle technology, the combination of experimental and simulation approaches is expected to improve the ability to obtain the maximum lung delivery and target the site of deposition in the lungs of individual patients.
(c)
Fig. 3. (a) CT axial view of lungs; (b) CT coronal view of lungs; (c) Human airways model created from CT images.
Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013
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(a-1)
(b-1)
(a-2)
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Fig. 4. (a) Velocity streamlines. (b) Deposited particles in each human airway. (1) An 82-year-old male patient with COPD; (2) A 69-year-old male patient with COPD.
Declaration of Competing Interest The authors report no declaration of interest. Acknowledgements The authors thank Hitachi Automotive Systems Measurement, Ltd, Japan for providing the Jethaler. We appreciate Siemens PLM Software Computational Dynamics K.K. and Materialise Japan for supporting the analysis of CFD and the creation of the airway model, respectively. We also thank Dr. Munehiro Maeda and Dr. Daisuke Maki in Nippon Life Hospital for helping us to take the
medical radiographical images in the form of computed tomographic data. T.R.S. acknowledges the support from NCN (Poland), Poland under the project No. 2018/29/B/ST8/00273.
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Please cite this article as: K. Kadota, T. R. Sosnowski, S. Tobita et al., A particle technology approach toward designing dry-powder inhaler formulations for personalized medicine in respiratory diseases, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2019.10.013