Development of computational models to predict delivery of inhalation drug powders: from deagglomeration in devices to deposition in airways

Information

  • Research Project
  • 9704116
  • ApplicationId
    9704116
  • Core Project Number
    U01FD006525
  • Full Project Number
    1U01FD006525-01
  • Serial Number
    006525
  • FOA Number
    RFA-FD-18-014
  • Sub Project Id
  • Project Start Date
    9/1/2018 - 5 years ago
  • Project End Date
    8/31/2021 - 2 years ago
  • Program Officer Name
    WALENGA, ROSS
  • Budget Start Date
    9/1/2018 - 5 years ago
  • Budget End Date
    8/31/2019 - 4 years ago
  • Fiscal Year
    2018
  • Support Year
    01
  • Suffix
  • Award Notice Date
    8/27/2018 - 5 years ago
Organizations

Development of computational models to predict delivery of inhalation drug powders: from deagglomeration in devices to deposition in airways

Project Summary/Abstract Background: Dry powder inhalation (DPI) devices represent up to 40% of total sales of the global inhalation market which was over US$ 23bn in 2016 and expected to increase to US$ 35bn by 2023. Because of the wide application and high profit margin of DPIs, there have been great efforts in the pharmaceutical industry to develop generic DPI devices. To be approved by the US FDA, a generic version needs to show bioequivalence (BE) to the corresponding brand DPI device. The current approach to establish BE is based on the aggregated weight of evidence which includes in vitro test, pharmacokinetic, and pharmacodynamic or clinical endpoint studies. Importantly the performance of a DPI device in the in vitro study should be linked to in vivo regional deposition. It is preferable that the aerodynamic particle size distribution (APSD) can be used to establish the in vitro-in vivo correlation (IVIVC). However, so far there is no enough evidence to support this idea due to difficulty to experimentally obtain in vivo data. Numerical modelling based on computational fluid dynamics (CFD) alone is also unable to predict the dynamics of particles due to non-spherical shape of powder fragments. Research Design: The goal of the project is to develop a coupled discrete element method (DEM) and CFD model to predict agglomeration and deagglomeration of carrier-API systems in DPIs. Combined with the latest imaging tools, advanced laser diagnostic techniques, and powder characterization technology feeding into the model, the CFD-DEM model can be used to quantitatively evaluate the effects of powder formulations and device design on the aerosol performance of DPIs. This model will also be linked to CFD-DPM to provide a three-way coupling to model powder airway deposition. This project includes 3 main phases. In Phase 1, a coupled CFD- DEM model will be developed by explicitly considering the key particle-particle and particle-flow interactions, including van der Waals and electrostatic forces. The multi-sphere approach will be used to mimic the non- spherical shape of particles. In Phase 2, the model will be vigorously validated by conducting detailed experimental analysis using novel measurement techniques developed by the team. Both agglomeration and deagglomeration of powders under different conditions will be investigated. In particular, fluid flow and APSD at the device mouthpiece will be linked to the deposition in mouth-throat region represented by USP induction port as well as optically accessible realistic collapsible mouth-throat model. In Phase 3, sensitivity tests will be carried out by changing powder formulations, device design and operation. Their effects on deagglomeration in DPI device and regional deposition in airways will be analysed, aiming to develop metrics for IVIVC. Significance: This project will provide an enabling technology which is able to quantitatively evaluate the in vitro efficiency and in vivo deposition of a DPI design for any given the powder formulation properties. A predictive, 3-way coupled DEM-CFD-DPM model based on in-depth understanding of the complex interactions between devices and formulations can provide detailed information at the particle scale, which will be useful for the BE study.

IC Name
FOOD AND DRUG ADMINISTRATION
  • Activity
    U01
  • Administering IC
    FD
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    190000
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    103
  • Ed Inst. Type
  • Funding ICs
    FDA:190000\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZFD1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    UNIVERSITY OF SYDNEY
  • Organization Department
  • Organization DUNS
    752389338
  • Organization City
    SYDNEY
  • Organization State
  • Organization Country
    AUSTRALIA
  • Organization Zip Code
    2006
  • Organization District
    AUSTRALIA