A quantitative approach to predicting lung deposition profiles of pharmaceutical powder aerosols.

Shadi Yaqoubi, Hak-Kim Chan, Ali Nokhodchi, Siavoush Dastmalchi, Ali Akbar Alizadeh, Mohammad Barzegar-Jalali, Khosro Adibkia, Hamed Hamishehkar

International journal of pharmaceutics 2021 Jun 01

filter terms:

Dry powder inhalers (DPI) are widely used systems for pulmonary delivery of therapeutics. The inhalation performance of DPIs is influenced by formulation features, inhaler device and inhalation pattern. The current review presents the affecting factors with great focus on powder characteristics which include particle size, shape, surface, density, hygroscopicity and crystallinity. The properties of a formulation are greatly influenced by a number of physicochemical factors of drug and added excipients. Since available particle engineering techniques result in particles with a set of modifications, it is difficult to distinguish the effect of an individual feature on powder deposition behavior. This necessitates developing a predictive model capable of describing all influential factors on dry powder inhaler delivery. Therefore, in the current study, a model was constructed to correlate the inhaler device properties, inhalation flow rate, particle characteristics and drug/excipient physicochemical properties with the resultant fine particle fraction. The r2 value of established correlation was 0.74 indicating 86% variability in FPF values is explained by the model with the mean absolute errors of 0.22 for the predicted values. The authors believe that this model is capable of predicting the lung deposition pattern of a formulation with an acceptable precision when the type of inhaler device, inhalation flow rate, physicochemical behavior of active and inactive ingredients and the particle characteristics of DPI formulations are considered. Copyright © 2021 Elsevier B.V. All rights reserved.

Citation

Shadi Yaqoubi, Hak-Kim Chan, Ali Nokhodchi, Siavoush Dastmalchi, Ali Akbar Alizadeh, Mohammad Barzegar-Jalali, Khosro Adibkia, Hamed Hamishehkar. A quantitative approach to predicting lung deposition profiles of pharmaceutical powder aerosols. International journal of pharmaceutics. 2021 Jun 01;602:120568