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

credit: Care2

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(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.