Respiratory drug delivery has matured in recent years to the extent that those working in formulation and device design of inhaled aerosols often desire tools that allow more sophisticated preclinical design optimization than has been the case in past years. As an increasingly useful tool in this regard, lung deposition models allow preclinical estimation of doses delivered to different regions of the respiratory tract with different inhalation and aerosol properties. Empirical models that are essentially curve fits to more accurately obtained data are readily used for this purpose but must be used with caution due to their inability to extrapolate outside the parameter range for which they were developed, the most severe such restriction being their inability to capture mouth-throat deposition accurately with dry powder and metered-dose inhalers. Empirical models are also unable to incorporate two-way coupled hygroscopic size changes, which are common with the new generation of aqueous delivery devices. Dynamical models that incorporate some of the aerosol dynamics have the potential to eliminate these issues. At present, dynamical models that reduce an idealized lung geometry to one dimension in space are most commonly used. The simplest of such models are the one-dimensional Lagrangian dynamical models (LDMs), which assume that the aerosol travels at the same velocity as a nondistorting plug of air traveling through an idealized lung geometry. More complex are the one-dimensional Eulerian dynamical models (EDMs), which instead solve for the aerosol behavior at a series of depths, x, into the lung at each point in time, t, during inhalation. Both types of dynamical models allow more confidence in estimating deposition with single-breath inhalation devices than do the empirical models, since the latter are based on deposition data with tidal breathing rather than single-breath inhalations. In addition, it is possible to capture two-way coupled hygroscopic effects with dynamical models.

At present both one-dimensional EDMs and LDMs use empirical models for mouth-throat deposition, so the aforementioned difficulty with correct prediction of mouth-throat deposition remains a concern for existing one-dimensional EDMs and LDMs.

More accurate predictions of localized deposition within airways can be obtained using computational fluid dynamics (CFD) methods to perform numerical simulation of the equations governing the aerosol and air motion in three-dimensional replicas of the air spaces in the lung. However, such an approach is currently hampered by the large computation times required to simulate a reasonable section of the respiratory tract and our present lack of knowledge of the three-dimensional geometry of the lung airspaces. As a result, such simulations are likely destined to remain solely a research tool for some time yet, being used largely to improve the abilities of simpler models, such as one-dimensional LDMs and EDMs. Future work in this direction may include the use of partial lung simulation (PLS) in the development of LDMs and EDMs for diseased lungs. In vivo validation of such improved deposition models is in itself a daunting task, requiring careful experimental design if meaningful results are to be obtained [35].

Estimating the doses depositing in different regions of the respiratory tract with a lung deposition model is only the first, and probably the most well-characterized, step in predicting the fate of an inhaled therapeutic agent. However, models that allow prediction of the subsequent steps are being developed, an example being airway surface liquid thickness models that allow estimation of drug concentrations in the mucus and periciliary liquid layers that line the tracheobronchial airways [1]. Combination of present-day lung deposition models with increasingly sophisticated models for predicting the behavior of aerosol particles subsequent to their deposition will occupy future research for some time to come.

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