Many modern drugs have low aqueous solubility, which can substantially reduce their therapeutic effectiveness. Tablets are compressed powders consisting of, among other ingredients, drug particles, which are often crystalline and need to dissolve to be absorbed in the intestines. When the aqueous solubility of the drug particles is low, the drug concentration in the gastrointestinal fluids will also be low, which hampers drug absorption. One way to overcome this problem is to formulate the drug as a so-called supersaturating drug delivery system. These systems can take many forms, one way is to crystallize a drug particle with a well-soluble molecule so that the drug in this form has a high aqueous solubility for rapid absorption. There is one downside though. Often the drug concentration gets sufficiently high so that stable drug particles can precipitate in the stomach or intestines of the patient, thereby lowering the drug concentration again. This project aims to shed a light on this phenomenon, which is important for better design of future drugs. Our group has mimicked this process in the lab for a model drug. We wonder how one can use these measurements to better understand the complete dissolution process. In this project, we would like to use this data to create a mathematical model that can predict the drug release as a function of common formulation parameters such as dose and composition. This model may need to be probabilistic, as the drug release can vary from patient to patient due to the inherent stochastic nature of the drug precipitation process. This project is most suitable for students with an interest in applied mathematics and/or mathematical programming. Laboratory experiments are not anticipated but optional for highly motivated students interested in lab work (safety training will be required for lab experiments).