Computational fluid dynamics (CFD) assisted performance evaluation of the Twincer™ disposable high-dose dry powder inhaler.

OBJECTIVES

To use computational fluid dynamics (CFD) for evaluating and understanding the performance of the high-dose disposable Twincer™ dry powder inhaler, as well as to learn the effect of design modifications on dose entrainment, powder dispersion and retention behaviour.

METHODS

Comparison of predicted flow and particle behaviour from CFD computations with experimental data obtained with cascade impactor and laser diffraction analysis.

KEY FINDINGS: Inhaler resistance, flow split, particle trajectories and particle residence times can well be predicted with CFD for a multiple classifier based inhaler like the Twincer™. CFD computations showed that the flow split of the Twincer™ is independent of the pressure drop across the inhaler and that the total flow rate can be decreased without affecting the dispersion efficacy or retention behaviour. They also showed that classifier symmetry can be improved by reducing the resistance of one of the classifier bypass channels, which for the current concept does not contribute to the swirl in the classifier chamber.

CONCLUSIONS

CFD is a highly valuable tool for development and optimisation of dry powder inhalers. CFD can assist adapting the inhaler design to specific physico-chemical properties of the drug formulation with respect to dispersion and retention behaviour.