CFD Models to aid the development of generic inhalation products

The summary for the CFD Models to aid the development of generic inhalation products grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the Food and Drug Administration, which is the U.S. government agency offering this grant.

CFD Models to aid the development of generic inhalation products: Current US Food and Drug Administration product specific guidance (PSG) bioequivalence (BE) recommendations for orally inhaled drug products such as metered dose inhalers (MDIs) and dry powder inhalers (DPIs) typically use a weight-of-evidence approach that includes in vitro studies, an in vivo pharmacokinetics (PK) study, and either an in vivo pharmacodynamics (PD) or comparative clinical endpoint (CCEP) study. To produce a generic MDI or DPI that is capable of passing all of these recommended studies, it would be useful to have an enhanced understanding of the relationships between in vitro study metrics and the rate and extent of drug delivery to the targeted lung tissue. Computational fluid dynamics (CFD) is a technique capable of predicting these relationships between in vitro study metrics and regional lung deposition. The purpose of this grant announcement is to use CFD to produce verified and validated predictions of regional lung deposition for at least one currently marketed MDI or DPI in human upper and lower airways. Once predictions are appropriately verified and validated using either in vitro or in vivo data, a parameter sensitivity analysis will be conducted to assess the biopredictive capabilities of relevant in vitro studies. For DPIs, discrete element modeling (DEM) may be considered as a means for predicting the effects of agglomeration and deagglomeration of carrier-active pharmaceutical ingredient combination particles on regional deposition and the relationships of those phenomena with APSD. For MDIs, it is preferred that formulations considered include at least three components.