Dry powder inhalers (DPIs) are a common therapeutic modality for lung diseases such as asthma, but they are also used to treat systemic diseases such as diabetes. Advantages of DPIs include their portable design and low manufacturing costs. Another advantage of DPIs is their breath activation, which makes them popular among patients. In a passive DPI drug is only released when the patient inhales. When the patient inhales, air flows through the device. The flow of air entrains a dry powder formulation inside the device and carries it to the lung.

Currently, no DPI exists which can deliver drug independent of the patient to the desired target site in the lung. This is because drug release depends on the patient’s inhalation manoeuvre. To maximize the effect of the treatment it is necessary to optimize DPIs to achieve drug delivery that (A) is independent of the inhalation manoeuvre and (B) is targeted to the correct site in the lung. Therefore, this thesis aims to apply numerical and experimental methods to optimize DPIs systematically.

First, two clinically justifiable cost functions have been developed corresponding to the DPI design objectives (A) and (B). An Eulerian-Eulerian (EE) computational fluid dynamics (CFD) approach has then been used to optimize a DPI entrainment geometry. Three different optimized entrainment geometries have been found corresponding to three different therapeutic applications.

Second, the CFD approach has been validated experimentally. This is the first experimental study to validate an EE CFD approach for DPI modelling.

Third, a personalized medicine approach to DPI design has been proposed. The development of this approach makes it possible to achieve the design objectives for patients with highly different lung functions.

Finally, an adaptive DPI with a variable bypass element has been developed. This DPI achieves design objectives (A) and (B) for patients with highly different lung functions with a single device. In contrast to the personalized medicine approach, there is no need to select the optimal amount of bypass, since the device adapts automatically.