This STTR Phase I proposal describes the development of a modeling framework that combines a mesoscopic model for hydrodynamics with dissolution kinetic models in order to accurately describe the dissolution behavior of drugs. The complexities of the drug dissolution problem have led to the development of empirical methodologies being the widespread practice in the pharmaceutical industry. However, because of a lack of mechanistic information the process has to be repeated for each new formulation, and no insights can be gained from the test. This process adds to the cost and increases the time to market for new drugs. Our approach uses the Lattice Boltzmann model, and uses an innovative modular approach of incorporating the detailed dissolution kinetics such that we can study drug dissolution under realistic hydrodynamic conditions. Further, our approach retains spatial information about the drug, and consequently we can study the effect of different morphologies (arrangement of components inside the tablet) on the dissolution behavior. We plan to develop this methodology and demonstrate its feasibility by comparing our model against published literature data on the dissolution behavior of salicyclic acid tablets. The project is a close collaboration between a software company (RES Group Inc) with deep expertise in chemical modeling, combustion engineering and numerical simulation and a theory group (Gersappe) at Stony Brook University with expertise in modeling ranging from microscopic Molecular Dynamics simulations to mesoscopic models such as the Lattice Boltzmann method and mean field methods.
This STTR Phase I proposal describes the development of a modeling framework that combines a mesoscopic model for hydrodynamics with dissolution kinetic models in order to accurately describe the dissolution behavior of drugs. This proposal aims to improve the efficiency of drug dissolution testing by developing a model based approach, along with associated workflow and tools that will enable pharmaceutical researchers to significantly reduce the cost and improve the time to market for new drugs.
