Development of Clinically Relevant in Vitro Performance Test for Generic OIDPs: Physiologically Relevant Models for Aerodynamic Particle Size Distribution Analysis

Archived

Food and Drug Administration

Description

For orally inhaled drug products (OIDPs), mouth-throat (MT) region behaves as a physiological filter that prevents significant fraction of inhaled drug from reaching the lungs. Hence, use of the models representing morphological features of MT region could help predict the drug loss in the MT region, and hence provide better predictability of lung deposition. Such realistic MT models, coupled with cascade impactors, could be used for characterization of aerodynamic particle size distribution (APSD), and can therefore be used as a pharmaceutical development tool for OIDPs. However, there are some challenges in adopting these modified cascade impactor methods. Although, several MT models have been proposed in the literature, with different geometries that produce different deposition patterns, there is lack of availability of the standardized MT model(s). Moreover, it has been demonstrated that coupling these MT models with realistic inhalation maneuvers in an impactor assembly can further improve in vivo predictability of these methods. However, there are no standardized inhalation maneuvers available for APSD characterization of different OIDPs. In addition, very limited information is available on the validity of the proposed MT models in terms of their in vivo predictability. Therefore, in order to build a predictive in vitro method for characterization of APSD, it is important to address the issues discussed above with aim of identifying optimal MT models that produce acceptable in vitro-in vivo correlation. ObjectivesThe goal of this project is to investigate if realistic physical MT models provide better predictability over pharmaceutical induction port assembly, for APSD characterization of OIDPs. Because there are different MT models proposed in the literature, in vivo predictability of several pre-screened MT models will be evaluated under different flow rate conditions, to select the optimal model(s). Upon successful completion, this research will provide a more realistic APSD characterization method that can be used as a pharmaceutical development tool in the early stages of OIDP development. Detailed DescriptionA predictive in vitro method will be developed to study the aerodynamic particle size distribution of the aerosolized drug particles. The study will consist of four phases. Phase 1: Selection of realistic MT models based on reported in vivo predictability and production/reproduction feasibility.Phase 2: Selection of representative OIDPs on the market for in vitro APSD evaluation using selected MT models. Phase 3: APSD characterization of the selected OIPDs products using cascade impactors USP apparatus 1 and 6 assembled with the selected throat models as well as USP induction port, under different flow rate conditions. Phase 4: Assessment of in vitro-in vivo correlation for each MT models and selection of optimal model/models.

Who can apply

  • State governments
  • County governments
  • City or township governments
  • Special district governments
  • Independent school districts
  • Public and State controlled institutions of higher education
  • Native American tribal governments (Federally recognized)
  • Public housing authorities / Indian housing authorities
  • Native American tribal organizations (other than Federally recognized)
  • Nonprofits with 501(c)(3) status (other than higher education)
  • Nonprofits without 501(c)(3) status (other than higher education)
  • Private institutions of higher education
  • Individuals
  • For-profit organizations other than small businesses
  • Small businesses
  • Others

Contact

Gladys Melendez-Bohler <br/>Grants Management Specialist <br/>Phone 301-827-7175
gladys.bohler@fda.hhs.gov

Key dates & funding
  • PostedMar 31, 2014
  • ClosesJun 3, 2014
  • Award floor$450,000
  • Award ceiling$500,000
  • Program funding$1,000,000
  • Expected awards5
  • CFDA93.103

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