Design of particle size distribution for custom dissolution profiles by solving the inverse problem

Dissolution testing is widely used to measure the rate of drug release and predict its in-vivo behavior. The release rate can be controlled by adjusting the particle size distribution (PSD). However, experimental investigation of various particle sizes requires many time-consuming experiments. To reduce the need for them, we propose an optimization framework to solve the inverse problem, i.e., design a PSD that results in a prescribed dissolution profile. The framework's computational core predicts a dissolution profile using a population balance model coupled with a mass balance equation, while the optimization algorithm obtains the inverse solution. The model was validated using mono- and multimodal particle populations of a reference compound (KCl). The validation resulted in a good agreement between the simulated and experimental data. This suggests that the usage of the framework can provide a fast determination of the required PSD, reducing the number of experiments needed.