Description
Advances in drug delivery increasingly rely on microfluidic systems for encapsulation, yet experimental optimization can be time-consuming and resource-intensive, requiring multiple iterations to identify suitable operating conditions. Computational fluid dynamics (CFD) provides a complementary tool, enabling systematic investigation of flow behavior, droplet formation, and overall device performance without extensive experimental trials. This study presents a combined numerical-experimental framework to develop a microfluidic system enabling drug encapsulation for controlled delivery. A multiphase CFD model was implemented to predict flow dynamics, interfacial behavior, and droplet formation mechanisms in order to identify operating conditions capable of producing target particle sizes. Experimental tests confirmed the predicted droplet formation regimes and particle dimensions, showing strong agreement with CFD predictions and demonstrating that the validated model can effectively support design decisions while reducing experimental iterations. The approach highlights the potential of CFD-driven optimization to improve microfluidic drug encapsulation systems.