In Silico Methods for Development of Generic Drug-Device Combination Orally Inhaled Drug Products

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.

Figure 1

Methodology used by Gavtash et al.38 to predict (a) fluid behavior in the metering and expansion chambers of ethanol/propellant mixtures and (b) transitional behavior through the spray orifice into an annular sheet exiting the orifice followed by droplet formation. HFA, hydrofluoroalkane; DSO, spray orifice diameter; H, annular liquid film thickness; Dgas, vapor phase diameter; Dlig, unstable ligament diameter; HFA134, 1,1,1,2‐Tetrafluoroethane; HFA227, 1,1,1,2,3,3,3‐Heptafluoropropane. Reprinted with permission of Taylor & Francis. Copyright © 2018 Taylor & Francis.

Figure 2

Predictions by Tian et al.47 using computational fluid dynamics (CFD) for mouth–throat, central lung, and peripheral lung deposition of an aqueous fenoterol solution as delivered by a Respimat Soft Mist Inhaler (Boehringer Ingelheim GmbH, Ingelheim am Rhein, Germany), where predictions are compared with in vivo gamma scintigraphy results from Newman et al.51 DF _CFD C, CFD predictions of deposition fraction in the central region; DF _{CFD I+P}, CFD predictions of deposition fraction in the intermediate and peripheral regions; DF _{CFD MT}, CFD predictions of deposition fraction in the mouth‐throat region; DF _{EXP C}, Experimental measurements of deposition fraction in the central region; DF _{EXP I+P}, Experimental measurements of deposition fraction in the intermediate and peripheral regions; DF _{EXP MT}, Experimental measurements of deposition fraction in the mouth‐throat region; LPM, Liters per minute; PIFR, Peak inspiratory flow rate. Reprinted with permission of Springer US. Copyright © 2015 Springer US.

Figure 3

Velocity contours and breakup patterns of agglomerate–agglomerate collision as predicted by Tong et al.59 at times of (a) 0, (b) 0.15, (c) 0.26, and (d) 0.33 seconds after particle release. Reprinted with permission of Elsevier. Copyright © 2016 Elsevier.

Figure 4

Plasma concentration predictions as provided by Vulović et al.70, given as function of time (t) in hours (h), after administration of nebulized amiloride hydrochloride when compared with in vivo data from Jones et al.85 where the pulmonary absorption constant values are either the default provided by Gastoplus (M1), 75% of the default value (M2), 50% of the default value (M3), or 25% of the default value (M4). Reprinted with permission of Elsevier. Copyright © 2018 Elsevier.

Figure 5

Qualitative description of the interaction between model influence and decision consequence on model risk.