Predicting Dissolution Kinetics for Active Pharmaceutical Ingredients on the Basis of Their Molecular Structures

In this work, the possibility of predicting absolute crystal dissolution rates for active pharmaceutical ingredients on the basis of only their corresponding molecular structures is presented. Toward this end, a combination of molecular dynamics (MD) and kinetic Monte Carlo (kMC) approaches is used. The dissolution processes are first investigated within a MD framework. Thereby, the benefit of applying a three-dimensional crystal representation is demonstrated. MD simulations are used to parametrize kMC simulations. A simple and universal way to define Markovian states and calculate rate constants for kMC simulations is proposed. Given the set of states and rate constants, a kMC approach provides a stochastic procedure to produce a state-to-state trajectory, representing a valid realization of the state-to-state dynamics, while at the same time significantly extending the range of length and time scales accessible to simulation. The results of combined MD and kMC simulations are presented for the dissolution of an aspirin crystal. A comparison with experimental data demonstrates the success of the approach.