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Eshaghi S, Khaleghi H, Maddahian R. Prediction of Transport and Deposition of Porous Particles in the Respiratory System Using Eulerian-Lagrangian Approach. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2024:e3873. [PMID: 39440676 DOI: 10.1002/cnm.3873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 08/12/2024] [Accepted: 09/15/2024] [Indexed: 10/25/2024]
Abstract
Deep lung delivery is crucial for respiratory disease treatment. Although nano and submicron particles exhibited a good deposition efficiency in deep regions of the lung, powder nonuniformity and particle agglomeration reduce their efficiency. Inhalation of porous particles (PPs) can overcome the mentioned challenges due to their larger size and low-density. The present study numerically investigates the deposition and penetration efficiency of orally inhaled PPs. A revised drag coefficient was implemented for PP transport. A realistic mouth-throat to the fifth generation of the lung was reconstructed from CT-scan images. A dilute suspension of uniformly distributed particles was considered at three inhalation flow rates (15, 30, and 45 L/min). Governing equations of the flow field and particle transport are solved using an Eulerian-Lagrangian approach. The results demonstrate that inhaling PPs significantly reduces the total and regional deposition of particles. There was also a critical porosity value under moderate and high inhalation flow rates for large PPs. Below this critical value, PP deposition efficiency substantially decreases. Additionally, it was also found that under low inhalation flow rates, the impact of porosity value is negligible. Almost 95% of the PPs penetrate the lower branches. These findings provide particle engineers and pharmaceutics with profound insight into developing novel inhalation techniques and drug delivery methods for deep lung delivery.
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Affiliation(s)
- Sajad Eshaghi
- Faculty of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran
| | - Hassan Khaleghi
- Faculty of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran
| | - Reza Maddahian
- Faculty of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran
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Rachapally A, Boddu R, Kollipara S, Ahmed T. Bioequivalence Requirements for Orally Inhaled and Nasal Drug Products and Use of Novel Physiologically Based Biopharmaceutics Modeling Approaches for Assessing In Vivo Performance. J Pharm Sci 2024:S0022-3549(24)00440-4. [PMID: 39414080 DOI: 10.1016/j.xphs.2024.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 10/04/2024] [Accepted: 10/04/2024] [Indexed: 10/18/2024]
Abstract
Orally inhaled and nasal drug products (OINDPs) are complex due to the interplay between the device, formulation, and patient characteristics. Establishing bioequivalence (BE) of OINDPs with reference is highly complex and require in vitro, in vivo pharmacokinetic and comparative clinical endpoint studies that are challenging to conduct. In order to increase the rate of submission and approval of generics, regulatory agencies are encouraging the use of alternative in vitro and in silico methodologies to replace complex in vivo studies. The present review attempts to summarize current understanding of alternative BE approaches for OINDPs. In vitro characterization studies required for establishing BE for OINDPs considering USFDA and EMA guidance's are detailed. In silico methods such as pulmonary compartmental transit and absorption (PCAT) with emphasis on model input parameters are portrayed. Further, two detailed case studies of inhalation nebulizer and nasal spray formulations are described where PCAT models are developed for predicting BE and local concentrations. Lastly, current understanding of such BE approaches from regulatory perspectives are discussed summarizing recent regulatory workshops and through collation of USFDA product specific guidance's for almost 70 drug products. Overall, this manuscript can act as ready-to-use guide to understand alternative approaches for establishing BE for OINDPs.
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Affiliation(s)
- Arvind Rachapally
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500 090, Telangana, India
| | - Rajkumar Boddu
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500 090, Telangana, India
| | - Sivacharan Kollipara
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500 090, Telangana, India
| | - Tausif Ahmed
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Bachupally, Medchal Malkajgiri District, Hyderabad 500 090, Telangana, India.
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Sinko PD, Parker L, Prahl Wittberg L, Bergström CAS. Estimation of the concentration boundary layer adjacent to a flat surface using computational fluid dynamics. Int J Pharm 2024; 653:123870. [PMID: 38401511 DOI: 10.1016/j.ijpharm.2024.123870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 01/28/2024] [Accepted: 01/29/2024] [Indexed: 02/26/2024]
Abstract
Dissolution-permeation (D/P) experiments are widely used during preclinical development due to producing results with better predictability than traditional monophasic experiments. However, it is difficult to compare absorption across in vitro setups given the propensity to only report apparent permeability. We therefore developed an approach to predict the concentration boundary layer for any D/P device by using computational fluid dynamics (CFD). The Navier-Stokes and continuity equation in 2D were solved numerically in MATLAB and by finite element methods in COMSOL v6.1 to predict the momentum [Formula: see text] and concentration ηg boundary layer for a flow over a flat plate, i.e. the classical Blasius boundary layer flow. A MATLAB algorithm was developed to calculate the edge of either boundary layer. The methodology to determine the concentration boundary layer based on Blasius's analysis provided an accurate estimate for both [Formula: see text] and ηg, resulting in, [Formula: see text] , at high Schmidt numbers (Sc ∼ 1000) within 14 % of the Blasius solution and 6.6 % of the accepted Schmidt number correlation ( [Formula: see text] ). The methodology based on the Blasius analysis of the concentration boundary layer using velocity and concentration profiles computed using CFD presented herein will enable characterization/analysis of complex D/P apparatuses used in preclinical development, where an analytical solution may not be available.
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Affiliation(s)
- Patrick D Sinko
- Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden
| | - Louis Parker
- FLOW, Department of Engineering Mechanics, Royal Institute of Technology, KTH, Osquars Backe 18, SE-100 44 Stockholm, Sweden
| | - Lisa Prahl Wittberg
- FLOW, Department of Engineering Mechanics, Royal Institute of Technology, KTH, Osquars Backe 18, SE-100 44 Stockholm, Sweden
| | - Christel A S Bergström
- Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden.
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Lancheros Porras KD, Alves IA, Novoa DMA. PBPK Modeling as an Alternative Method of Interspecies Extrapolation that Reduces the Use of Animals: A Systematic Review. Curr Med Chem 2024; 31:102-126. [PMID: 37031391 DOI: 10.2174/0929867330666230408201849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/03/2023] [Accepted: 02/03/2023] [Indexed: 04/10/2023]
Abstract
INTRODUCTION Physiologically based pharmacokinetic (PBPK) modeling is a computational approach that simulates the anatomical structure of the studied species and presents the organs and tissues as compartments interconnected by arterial and venous blood flows. AIM The aim of this systematic review was to analyze the published articles focused on the development of PBPK models for interspecies extrapolation in the disposition of drugs and health risk assessment, presenting to this modeling an alternative to reduce the use of animals. METHODS For this purpose, a systematic search was performed in PubMed using the following search terms: "PBPK" and "Interspecies extrapolation". The revision was performed according to PRISMA guidelines. RESULTS In the analysis of the articles, it was found that rats and mice are the most commonly used animal models in the PBPK models; however, most of the physiological and physicochemical information used in the reviewed studies were obtained from previous publications. Additionally, most of the PBPK models were developed to extrapolate pharmacokinetic parameters to humans and the main application of the models was for toxicity testing. CONCLUSION PBPK modeling is an alternative that allows the integration of in vitro and in silico data as well as parameters reported in the literature to predict the pharmacokinetics of chemical substances, reducing in large quantity the use of animals that are required in traditional studies.
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Xu Y, Li H, Sun N, Yao B, Dai W, Wang J, Si S, Liu S, Jiang L. Dry Powder Formulations for Inhalation Require a Smaller Aerodynamic Diameter for Usage at High Altitude. J Pharm Sci 2023; 112:2655-2666. [PMID: 37595750 DOI: 10.1016/j.xphs.2023.08.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/14/2023] [Accepted: 08/14/2023] [Indexed: 08/20/2023]
Abstract
BACKGROUND High Altitude Pulmonary Edema (HAPE) seriously threatens the health of people at high altitudes. There are drug treatments for HAPE, and dry powder formulations (DPFs) represent a rapid and accessible delivery vehicle for these drugs. However, there are presently no reports on the inhalability of DPFs in low-pressure environments. Given the reduced atmospheric pressure typical at high altitudes, conventional DPFs might not be suitable for inhalation. Therefore, it is necessary to elucidate the deposition behaviors of dry powder in the respiratory tract at low pressure, as well as to improve their pulmonary deposition efficiency via adjustments to their formulation and design. METHODS The effect of air pressure, inspiratory velocity, and particle properties (such as size, density, and aerodynamic diameter) on pulmonary deposition of DPFs was calculated by a computational fluid dynamics (CFD)-coupled discrete phase model. DPFs of various aerodynamic diameters were prepared by spray drying, and the inhalability of these DPFs in a low-pressure environment was evaluated in mice. Finally, a mouse model of HAPE was established, and the treatment of HAPE by nifedipine-loaded DPFs with small aerodynamic diameter was validated. RESULTS CFD results showed that low pressure decreased the deposition of DPFs in the lungs. At 0.5 standard atmosphere, DPFs with aerodynamic diameter of ∼2.0 μm could not enter the lower respiratory tract; however, a decrease in the physical diameter, density, and, consequently, the aerodynamic diameter of the DPFs was able to enhance pulmonary deposition of these powders. To validate the CFD results, three kinds of dry powder with aerodynamic diameters of 0.66, 0.98, and 2.00 μm were prepared by spray drying. Powders with smaller aerodynamic diameter could be inhaled into the lungs of mice more effectively, and, consequently could ameliorate the progression of HAPE more effectively than conventional powders. These results were consistent with the CFD results. CONCLUSIONS Low atmospheric pressure can prevent the pulmonary deposition of DPFs at high altitudes. Compared with conventional DPFs, powders with smaller aerodynamic diameter can be effectively inhaled at these pressures and thus might be more suitable for the treatment the HAPE.
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Affiliation(s)
- Ya Xu
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Huiyang Li
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Nan Sun
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China; The Affiliated Lianyungang Oriental Hospital of Xuzhou Medical University, Lianyungang 222042, China
| | - Bingmei Yao
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Wenjin Dai
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Jian Wang
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Sujia Si
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Shuo Liu
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China
| | - Liqun Jiang
- School of Pharmacy, Xuzhou Medical University, Xuzhou 221009, China.
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Numerical Modeling of Particle Dynamics Inside a Dry Powder Inhaler. Pharmaceutics 2022; 14:pharmaceutics14122591. [PMID: 36559084 PMCID: PMC9783107 DOI: 10.3390/pharmaceutics14122591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/11/2022] [Accepted: 11/18/2022] [Indexed: 11/26/2022] Open
Abstract
The development of novel dry powders for dry powder inhalers (DPIs) requires the in vitro assessment of DPI aerodynamic performance. As a potential complementary method, in silico numerical simulations can provide additional information about the mechanisms that guide the particles and their behavior inside DPIs. The aim of this study was to apply computational fluid dynamics (CFDs) coupled with a discrete phase model (DPM) to describe the forces and particle trajectories inside the RS01® as a model DPI device. The methodology included standard fluid flow equations but also additional equations for the particle sticking mechanism, as well as particle behavior after contacting the DPI wall surface, including the particle detachment process. The results show that the coefficient of restitution between the particle and the impact surface does not have a high impact on the results, meaning that all tested combinations gave similar output efficiencies and particle behaviors. No sliding or rolling mechanisms were observed for the particle detachment process, meaning that simple bouncing off or deposition particle behavior is present inside DPIs. The developed methodology can serve as a basis for the additional understanding of the particles' behavior inside DPIs, which is not possible using only in vitro experiments; this implies the possibility of increasing the efficiency of DPIs.
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Newman B, Babiskin A, Bielski E, Boc S, Dhapare S, Fang L, Feibus K, Kaviratna A, Li BV, Luke MC, Ma T, Spagnola M, Walenga RL, Wang Z, Zhao L, El-Gendy N, Bertha CM, Abd El-Shafy M, Gaglani DK. Scientific and regulatory activities initiated by the U.S. Food and drug administration to foster approvals of generic dry powder inhalers: Bioequivalence perspective. Adv Drug Deliv Rev 2022; 190:114526. [PMID: 36067967 DOI: 10.1016/j.addr.2022.114526] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/26/2022] [Accepted: 08/30/2022] [Indexed: 01/24/2023]
Abstract
Regulatory science for generic dry powder inhalers (DPIs) in the United States (U.S.) has evolved over the last decade. In 2013, the U.S. Food and Drug Administration (FDA) published the draft product-specific guidance (PSG) for fluticasone propionate and salmeterol xinafoate inhalation powder. This was the first PSG for a DPI available in the U.S., which provided details on a weight-of-evidence approach for establishing bioequivalence (BE). A variety of research activities including in vivo and in vitro studies were used to support these recommendations, which have led to the first approval of a generic DPI in the U.S. for fluticasone propionate and salmeterol xinafoate inhalation powder in January of 2019. This review describes the scientific and regulatory activities that have been initiated by FDA to support the current BE recommendations for DPIs that led to the first generic DPI approvals, as well as research with novel in vitro and in silico methods that may potentially facilitate generic DPI development and approval.
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Affiliation(s)
- Bryan Newman
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Andrew Babiskin
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Elizabeth Bielski
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Susan Boc
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Sneha Dhapare
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Lanyan Fang
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Katharine Feibus
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Anubhav Kaviratna
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Bing V Li
- Office of Bioequivalence, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Markham C Luke
- Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Tian Ma
- Division of Bioequivalence I, Office of Bioequivalence, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Michael Spagnola
- Division of Clinical Safety and Surveillance, Office of Safety and Clinical Evaluation, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Ross L Walenga
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.
| | - Zhong Wang
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Liang Zhao
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Nashwa El-Gendy
- Division of Immediate and Modified Release Drug Products III, Office of Lifecycle Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Craig M Bertha
- Division of New Drug Products II, Office of New Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Mohammed Abd El-Shafy
- Division of Immediate and Modified Release Drug Products III, Office of Lifecycle Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Dhaval K Gaglani
- Division of Immediate and Modified Release Drug Products III, Office of Lifecycle Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
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Wang W, Ouyang D. Opportunities and challenges of physiologically based pharmacokinetic modeling in drug delivery. Drug Discov Today 2022; 27:2100-2120. [PMID: 35452792 DOI: 10.1016/j.drudis.2022.04.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/03/2022] [Accepted: 04/13/2022] [Indexed: 12/15/2022]
Abstract
Physiologically based pharmacokinetic (PBPK) modeling is an important in silico tool to bridge drug properties and in vivo PK behaviors during drug development. Over the recent decade, the PBPK method has been largely applied to drug delivery systems (DDS), including oral, inhaled, transdermal, ophthalmic, and complex injectable products. The related therapeutic agents have included small-molecule drugs, therapeutic proteins, nucleic acids, and even cells. Simulation results have provided important insights into PK behaviors of new dosage forms, which strongly support drug regulation. In this review, we comprehensively summarize recent progress in PBPK applications in drug delivery, which shows large opportunities for facilitating drug development. In addition, we discuss the challenges of applying this methodology from a practical viewpoint.
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Affiliation(s)
- Wei Wang
- Institute of Chinese Medical Sciences (ICMS), State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau, China; Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Macau, China
| | - Defang Ouyang
- Institute of Chinese Medical Sciences (ICMS), State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau, China; Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Macau, China.
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9
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Comparative Assessment of In Vitro and In Silico Methods for Aerodynamic Characterization of Powders for Inhalation. Pharmaceutics 2021; 13:pharmaceutics13111831. [PMID: 34834247 PMCID: PMC8619946 DOI: 10.3390/pharmaceutics13111831] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 10/25/2021] [Accepted: 10/28/2021] [Indexed: 11/16/2022] Open
Abstract
In vitro assessment of dry powders for inhalation (DPIs) aerodynamic performance is an inevitable test in DPI development. However, contemporary trends in drug development also implicate the use of in silico methods, e.g., computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM). The aim of this study was to compare the designed CFD-DPM outcomes with the results of three in vitro methods for aerodynamic assessment of solid lipid microparticle DPIs. The model was able to simulate particle-to-wall sticking and estimate fractions of particles that stick or bounce off the inhaler's wall; however, we observed notable differences between the in silico and in vitro results. The predicted emitted fractions (EFs) were comparable to the in vitro determined EFs, whereas the predicted fine particle fractions (FPFs) were generally lower than the corresponding in vitro values. In addition, CFD-DPM predicted higher mass median aerodynamic diameter (MMAD) in comparison to the in vitro values. The outcomes of different in vitro methods also diverged, implying that these methods are not interchangeable. Overall, our results support the utility of CFD-DPM in the DPI development, but highlight the need for additional improvements in these models to capture all the key processes influencing aerodynamic performance of specific DPIs.
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10
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Chow MYT, Tai W, Chang RYK, Chan HK, Kwok PCL. In vitro-in vivo correlation of cascade impactor data for orally inhaled pharmaceutical aerosols. Adv Drug Deliv Rev 2021; 177:113952. [PMID: 34461200 DOI: 10.1016/j.addr.2021.113952] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 08/24/2021] [Accepted: 08/24/2021] [Indexed: 12/11/2022]
Abstract
In vitro-in vivo correlation is the establishment of a predictive relationship between in vitro and in vivo data. In the context of cascade impactor results of orally inhaled pharmaceutical aerosols, this involves the linking of parameters such as the emitted dose, fine particle dose, fine particle fraction, and mass median aerodynamic diameter to in vivo lung deposition from scintigraphy data. If the dissolution and absorption processes after deposition are adequately understood, the correlation may be extended to the pharmacokinetics and pharmacodynamics of the delivered drugs. Correlation of impactor data to lung deposition is a relatively new research area that has been gaining recent interest. Although few in number, experiments and meta-analyses have been conducted to examine such correlations. An artificial neural network approach has also been employed to analyse the complex relationships between multiple factors and responses. However, much research is needed to generate more data to obtain robust correlations. These predictive models will be useful in improving the efficiency in product development by reducing the need of expensive and lengthy clinical trials.
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11
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Kiwumulo HF, Muwonge H, Ibingira C, Kirabira JB, Ssekitoleko RT. A systematic review of modeling and simulation approaches in designing targeted treatment technologies for Leukemia Cancer in low and middle income countries. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:8149-8173. [PMID: 34814293 DOI: 10.3934/mbe.2021404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Virtual experimentation is a widely used approach for predicting systems behaviour especially in situations where resources for physical experiments are very limited. For example, targeted treatment inside the human body is particularly challenging, and as such, modeling and simulation is utilised to aid planning before a specific treatment is administered. In such approaches, precise treatment, as it is the case in radiotherapy, is used to administer a maximum dose to the infected regions while minimizing the effect on normal tissue. Complicated cancers such as leukemia present even greater challenges due to their presentation in liquid form and not being localised in one area. As such, science has led to the development of targeted drug delivery, where the infected cells can be specifically targeted anywhere in the body. Despite the great prospects and advances of these modeling and simulation tools in the design and delivery of targeted drugs, their use by Low and Middle Income Countries (LMICs) researchers and clinicians is still very limited. This paper therefore reviews the modeling and simulation approaches for leukemia treatment using nanoparticles as an example for virtual experimentation. A systematic review from various databases was carried out for studies that involved cancer treatment approaches through modeling and simulation with emphasis to data collected from LMICs. Results indicated that whereas there is an increasing trend in the use of modeling and simulation approaches, their uptake in LMICs is still limited. According to the review data collected, there is a clear need to employ these tools as key approaches for the planning of targeted drug treatment approaches.
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Affiliation(s)
| | - Haruna Muwonge
- Department of Medical Physiology, Makerere University, Kampala, Uganda
| | - Charles Ibingira
- Department of Human Anatomy, Makerere University, Kampala, Uganda
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Zanin M, Aitya NA, Basilio J, Baumbach J, Benis A, Behera CK, Bucholc M, Castiglione F, Chouvarda I, Comte B, Dao TT, Ding X, Pujos-Guillot E, Filipovic N, Finn DP, Glass DH, Harel N, Iesmantas T, Ivanoska I, Joshi A, Boudjeltia KZ, Kaoui B, Kaur D, Maguire LP, McClean PL, McCombe N, de Miranda JL, Moisescu MA, Pappalardo F, Polster A, Prasad G, Rozman D, Sacala I, Sanchez-Bornot JM, Schmid JA, Sharp T, Solé-Casals J, Spiwok V, Spyrou GM, Stalidzans E, Stres B, Sustersic T, Symeonidis I, Tieri P, Todd S, Van Steen K, Veneva M, Wang DH, Wang H, Wang H, Watterson S, Wong-Lin K, Yang S, Zou X, Schmidt HH. An Early Stage Researcher's Primer on Systems Medicine Terminology. NETWORK AND SYSTEMS MEDICINE 2021; 4:2-50. [PMID: 33659919 PMCID: PMC7919422 DOI: 10.1089/nsm.2020.0003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/27/2020] [Indexed: 12/19/2022] Open
Abstract
Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.
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Affiliation(s)
- Massimiliano Zanin
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
| | - Nadim A.A. Aitya
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - José Basilio
- Center for Physiology and Pharmacology, Institute of Vascular Biology and Thrombosis Research, Medical University of Vienna, Vienna, Austria
| | - Jan Baumbach
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Arriel Benis
- Faculty of Technology Management, Holon Institute of Technology (HIT), Holon, Israel
| | - Chandan K. Behera
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Magda Bucholc
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Filippo Castiglione
- CNR National Research Council, IAC Institute for Applied Computing, Rome, Italy
| | - Ioanna Chouvarda
- Lab of Computing, Medical Informatics, and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Blandine Comte
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Tien-Tuan Dao
- Biomechanics and Bioengineering Laboratory (UMR CNRS 7338), Université de Technologie de Compiègne, Compiègne, France
- Labex MS2T “Control of Technological Systems-of-Systems,” CNRS and Université de Technologie de Compiègne, Compiègne, France
| | - Xuemei Ding
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Estelle Pujos-Guillot
- Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France
| | - Nenad Filipovic
- Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia
- Bioengineering Research and Development Center (BioIRC), Kragujevac, Serbia
- Steinbeis Advanced Risk Technologies Institute doo Kragujevac, Kragujevac, Serbia
| | - David P. Finn
- Pharmacology and Therapeutics, School of Medicine, Galway Neuroscience Centre, National University of Ireland, Galway, Republic of Ireland
| | - David H. Glass
- School of Computing, Ulster University, Ulster, United Kingdom
| | - Nissim Harel
- Faculty of Sciences, Holon Institute of Technology (HIT), Holon, Israel
| | - Tomas Iesmantas
- Department of Mathematics and Natural Sciences, Kaunas University of Technology, Kaunas, Lithuania
| | - Ilinka Ivanoska
- Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Macedonia
| | - Alok Joshi
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Karim Zouaoui Boudjeltia
- Laboratory of Experimental Medicine (ULB 222), Medicine Faculty, Université libre de Bruxelles, CHU de Charleroi, Charleroi, Belgium
| | - Badr Kaoui
- Biomechanics and Bioengineering Laboratory (UMR CNRS 7338), Université de Technologie de Compiègne, Compiègne, France
- Labex MS2T “Control of Technological Systems-of-Systems,” CNRS and Université de Technologie de Compiègne, Compiègne, France
| | - Daman Kaur
- Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, Ulster, United Kingdom
| | - Liam P. Maguire
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Paula L. McClean
- Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, Ulster, United Kingdom
| | - Niamh McCombe
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - João Luís de Miranda
- Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Portalegre, Portalegre, Portugal
- Centro de Recursos Naturais e Ambiente (CERENA), Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
| | | | | | - Annikka Polster
- Centre for Molecular Medicine Norway (NCMM), Forskningparken, Oslo, Norway
| | - Girijesh Prasad
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Damjana Rozman
- Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Ioan Sacala
- Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania
| | - Jose M. Sanchez-Bornot
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Johannes A. Schmid
- Center for Physiology and Pharmacology, Institute of Vascular Biology and Thrombosis Research, Medical University of Vienna, Vienna, Austria
| | - Trevor Sharp
- Department of Pharmacology, University of Oxford, Oxford, United Kingdom
| | - Jordi Solé-Casals
- Data and Signal Processing Research Group, University of Vic–Central University of Catalonia, Vic, Spain
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- College of Artificial Intelligence, Nankai University, Tianjin, China
| | - Vojtěch Spiwok
- Department of Biochemistry and Microbiology, University of Chemistry and Technology, Prague, Czech Republic
| | - George M. Spyrou
- The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Egils Stalidzans
- Computational Systems Biology Group, Institute of Microbiology and Biotechnology, University of Latvia, Riga, Latvia
| | - Blaž Stres
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia
- Department of Automation, Biocybernetics and Robotics, Jozef Stefan Institute, Ljubljana, Slovenia
| | - Tijana Sustersic
- Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia
- Bioengineering Research and Development Center (BioIRC), Kragujevac, Serbia
- Steinbeis Advanced Risk Technologies Institute doo Kragujevac, Kragujevac, Serbia
| | - Ioannis Symeonidis
- Center for Research and Technology Hellas, Hellenic Institute of Transport, Thessaloniki, Greece
| | - Paolo Tieri
- CNR National Research Council, IAC Institute for Applied Computing, Rome, Italy
| | - Stephen Todd
- Altnagelvin Area Hospital, Western Health and Social Care Trust, Altnagelvin, United Kingdom
| | - Kristel Van Steen
- BIO3-Systems Genetics, GIGA-R, University of Liege, Liege, Belgium
- BIO3-Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | | | - Da-Hui Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, and School of Systems Science, Beijing Normal University, Beijing, China
| | - Haiying Wang
- School of Computing, Ulster University, Ulster, United Kingdom
| | - Hui Wang
- School of Computing, Ulster University, Ulster, United Kingdom
| | - Steven Watterson
- Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry, United Kingdom
| | - KongFatt Wong-Lin
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Su Yang
- Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Ulster, United Kingdom
| | - Xin Zou
- Shanghai Centre for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Harald H.H.W. Schmidt
- Faculty of Health, Medicine & Life Science, Maastricht University, Maastricht, The Netherlands
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13
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Zheng Z, Leung SSY, Gupta R. Flow and Particle Modelling of Dry Powder Inhalers: Methodologies, Recent Development and Emerging Applications. Pharmaceutics 2021; 13:189. [PMID: 33535512 PMCID: PMC7912775 DOI: 10.3390/pharmaceutics13020189] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/22/2021] [Accepted: 01/27/2021] [Indexed: 11/16/2022] Open
Abstract
Dry powder inhaler (DPI) is a device used to deliver a drug in dry powder form to the lungs. A wide range of DPI products is currently available, with the choice of DPI device largely depending on the dose, dosing frequency and powder properties of formulations. Computational fluid dynamics (CFD), together with various particle motion modelling tools, such as discrete particle methods (DPM) and discrete element methods (DEM), have been increasingly used to optimise DPI design by revealing the details of flow patterns, particle trajectories, de-agglomerations and depositions within the device and the delivery paths. This review article focuses on the development of the modelling methodologies of flow and particle behaviours in DPI devices and their applications to device design in several emerging fields. Various modelling methods, including the most recent multi-scale approaches, are covered and the latest simulation studies of different devices are summarised and critically assessed. The potential and effectiveness of the modelling tools in optimising designs of emerging DPI devices are specifically discussed, such as those with the features of high-dose, pediatric patient compatibility and independency of patients' inhalation manoeuvres. Lastly, we summarise the challenges that remain to be addressed in DPI-related fluid and particle modelling and provide our thoughts on future research direction in this field.
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Affiliation(s)
- Zhanying Zheng
- Center for Turbulence Control, Harbin Institute of Technology, Shenzhen 518055, China
| | - Sharon Shui Yee Leung
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong;
| | - Raghvendra Gupta
- Department of Chemical Engineering, Indian Institute of Technology Guwahati, Assam 781039, India;
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14
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Shi C, Ignjatović J, Liu T, Han M, Cun D, Đuriš J, Yang M, Cvijić S. In vitro - in vivo - in silico approach in the development of inhaled drug products: Nanocrystal-based formulations with budesonide as a model drug. Asian J Pharm Sci 2021; 16:350-362. [PMID: 34276823 PMCID: PMC8261257 DOI: 10.1016/j.ajps.2020.12.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 11/16/2020] [Accepted: 12/03/2020] [Indexed: 02/07/2023] Open
Abstract
This study aims to understand the absorption patterns of three different kinds of inhaled formulations via in silico modeling using budesonide (BUD) as a model drug. The formulations investigated in this study are: (i) commercially available micronized BUD mixed with lactose (BUD-PT), (ii) BUD nanocrystal suspension (BUD-NC), (iii) BUD nanocrystals embedded hyaluronic acid microparticles (BUD-NEM). The deposition patterns of the three inhaled formulations in the rats’ lungs were determined in vivo and in silico predicted, which were used as inputs in GastroPlus™ software to predict drug absorption following aerosolization of the tested formulations. BUD pharmacokinetics, estimated based on intravenous data in rats, was used to establish a drug-specific in silico absorption model. The BUD-specific in silico model revealed that drug pulmonary solubility and absorption rate constant were the key factors affecting pulmonary absorption of BUD-NC and BUD-NEM, respectively. In the case of BUD-PT, the in silico model revealed significant gastrointestinal absorption of BUD, which could be overlooked by traditional in vivo experimental observation. This study demonstrated that in vitro-in vivo-in silico approach was able to identify the key factors that influence the absorption of different inhaled formulations, which may facilitate the development of orally inhaled formulations with different drug release/absorption rates.
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Affiliation(s)
- Changzhi Shi
- Wuya College of Innovation, Shenyang Pharmaceutical University, Wenhua Road No. 103, 110016 Shenyang, China
| | - Jelisaveta Ignjatović
- Department of Pharmaceutical Technology and Cosmetology, University of Belgrade-Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Tingting Liu
- Wuya College of Innovation, Shenyang Pharmaceutical University, Wenhua Road No. 103, 110016 Shenyang, China
| | - Meihua Han
- Wuya College of Innovation, Shenyang Pharmaceutical University, Wenhua Road No. 103, 110016 Shenyang, China
| | - Dongmei Cun
- Wuya College of Innovation, Shenyang Pharmaceutical University, Wenhua Road No. 103, 110016 Shenyang, China
| | - Jelena Đuriš
- Department of Pharmaceutical Technology and Cosmetology, University of Belgrade-Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
| | - Mingshi Yang
- Wuya College of Innovation, Shenyang Pharmaceutical University, Wenhua Road No. 103, 110016 Shenyang, China.,Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark
| | - Sandra Cvijić
- Department of Pharmaceutical Technology and Cosmetology, University of Belgrade-Faculty of Pharmacy, Vojvode Stepe 450, 11221 Belgrade, Serbia
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15
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Cvijić S, Ignjatović J, Parojčić J, Ibrić S. The emerging role of physiologically-based pharmacokinetic/biopharmaceutics modeling in formulation development. ARHIV ZA FARMACIJU 2021. [DOI: 10.5937/arhfarm71-32479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
Computer-based (in silico) modeling & simulation tools have been embraced in different fields of pharmaceutics for a variety of applications. Among these, physiologically-based pharmacokinetic/biopharmaceutics modeling (PBPK/PBBM) emerged as a particularly useful tool in formulation development. PBPK/PBBM facilitated strategies have been increasingly evaluated over the past few years, as demonstrated by several reports from the pharmaceutical industry, and a number of research and review papers on this subject. Also, the leading regulatory authorities have recently issued guidance on the use of PBPK modeling in formulation design. In silico PBPK models can comprise different dosing routes (oral, intraoral, parenteral, inhalation, ocular, dermal etc.), although the majority of published examples refer to modeling of oral drugs performance. In order to facilitate the use of PBPK modeling tools, a couple of companies have launched commercially available software such as GastroPlus™, Simcyp™ PBPK Simulator and PK-Sim®. This paper highlights various application fields of PBPK/PBBM modeling, along with the basic principles, advantages and limitations of this approach, and provides relevant examples to demonstrate the practical utility of modeling & simulation tools in different stages of formulation development.
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16
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Mehta PP, Ghoshal D, Pawar AP, Kadam SS, Dhapte-Pawar VS. Recent advances in inhalable liposomes for treatment of pulmonary diseases: Concept to clinical stance. J Drug Deliv Sci Technol 2020. [DOI: 10.1016/j.jddst.2020.101509] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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17
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Advanced in vitro lung-on-chip platforms for inhalation assays: From prospect to pipeline. Eur J Pharm Biopharm 2019; 144:11-17. [PMID: 31499161 DOI: 10.1016/j.ejpb.2019.09.006] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 09/04/2019] [Accepted: 09/06/2019] [Indexed: 01/14/2023]
Abstract
With rapid advances in micro-fabrication processes and the availability of biologically-relevant lung cells, the development of lung-on-chip platforms is offering novel avenues for more realistic inhalation assays in pharmaceutical research, and thereby an opportunity to depart from traditional in vitro lung assays. As advanced models capturing the cellular pulmonary make-up at an air-liquid interface (ALI), lung-on-chips emulate both morphological features and biological functionality of the airway barrier with the ability to integrate respiratory breathing motions and ensuing tissue strains. Such in vitro systems allow importantly to mimic more realistic physiological respiratory flow conditions, with the opportunity to integrate physically-relevant transport determinants of aerosol inhalation therapy, i.e. recapitulating the pathway from airborne flight to deposition on the airway lumen. In this short opinion, we discuss such points and describe how these attributes are paving new avenues for exploring improved drug carrier designs (e.g. shape, size, etc.) and targeting strategies (e.g. conductive vs. respiratory regions) amongst other. We argue that while technical challenges still lie along the way in rendering in vitro lung-on-chip platforms more widespread across the general pharmaceutical research community, significant momentum is steadily underway in accelerating the prospect of establishing these as in vitro "gold standards".
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18
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Walenga RL, Babiskin AH, Zhao L. In Silico Methods for Development of Generic Drug-Device Combination Orally Inhaled Drug Products. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 8:359-370. [PMID: 31044532 PMCID: PMC6618094 DOI: 10.1002/psp4.12413] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 04/07/2019] [Indexed: 12/03/2022]
Abstract
The development of generic, single‐entity, drug–device combination products for orally inhaled drug products is challenging in part because of the complex nature of device design characteristics and the difficulties associated with establishing bioequivalence for a locally acting drug product delivered to the site of action in the lung. This review examines in silico models that may be used to support the development of generic orally inhaled drug products and how model credibility may be assessed.
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Affiliation(s)
- Ross L Walenga
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Andrew H Babiskin
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Liang Zhao
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
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19
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Bourganis V, Kammona O, Alexopoulos A, Kiparissides C. Recent advances in carrier mediated nose-to-brain delivery of pharmaceutics. Eur J Pharm Biopharm 2018; 128:337-362. [PMID: 29733950 DOI: 10.1016/j.ejpb.2018.05.009] [Citation(s) in RCA: 175] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 03/26/2018] [Accepted: 05/03/2018] [Indexed: 01/06/2023]
Abstract
Central nervous system (CNS) disorders (e.g., multiple sclerosis, Alzheimer's disease, etc.) represent a growing public health issue, primarily due to the increased life expectancy and the aging population. The treatment of such disorders is notably elaborate and requires the delivery of therapeutics to the brain in appropriate amounts to elicit a pharmacological response. However, despite the major advances both in neuroscience and drug delivery research, the administration of drugs to the CNS still remains elusive. It is commonly accepted that effectiveness-related issues arise due to the inability of parenterally administered macromolecules to cross the Blood-Brain Barrier (BBB) in order to access the CNS, thus impeding their successful delivery to brain tissues. As a result, the direct Nose-to-Brain delivery has emerged as a powerful strategy to circumvent the BBB and deliver drugs to the brain. The present review article attempts to highlight the different experimental and computational approaches pursued so far to attain and enhance the direct delivery of therapeutic agents to the brain and shed some light on the underlying mechanisms involved in the pathogenesis and treatment of neurological disorders.
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Affiliation(s)
- Vassilis Bourganis
- Department of Chemical Engineering, Aristotle University of Thessaloniki, P.O. Box 472, 54124 Thessaloniki, Greece
| | - Olga Kammona
- Chemical Process & Energy Resources Institute, Centre for Research and Technology Hellas, P.O. Box 60361, 57001 Thessaloniki, Greece
| | - Aleck Alexopoulos
- Chemical Process & Energy Resources Institute, Centre for Research and Technology Hellas, P.O. Box 60361, 57001 Thessaloniki, Greece
| | - Costas Kiparissides
- Department of Chemical Engineering, Aristotle University of Thessaloniki, P.O. Box 472, 54124 Thessaloniki, Greece; Chemical Process & Energy Resources Institute, Centre for Research and Technology Hellas, P.O. Box 60361, 57001 Thessaloniki, Greece.
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