The conformational spaces of active pharmaceutical ingredients (APIs) are of great interest. Many clinically and economically relevant drug molecules are highly flexible, capable of changing shape readily in biological environments, as well as displaying conformational polymorphism in the solid state . This polymorphism is particularly important to the drug design and manufacturing process, as the pharmacological properties of APIs can depend very strongly on the crystal's polymorphism . That the environment of a molecule impacts its conformational landscape is accepted ; however, a systematic method for the mapping and understanding of the conformational spaces of APIs is lacking , partly due to the inherent high-dimensionality of these spaces . Thus, a general mechanistic understanding of the impact of conformational states on crystallization does not exist. Here, we present a workflow that combines enhanced sampling molecular dynamics techniques with densitybased clustering methods to systematically explore the conformational free energy surface (FES) of a small, organic API. A molecule's conformation can be defined using the values of the molecule's freely rotatable dihedral angles (henceforth referred to as torsions). The conformation space is, therefore, always bounded and periodic in all dimensions. Veber's rules , a set of heuristics initially designed to predict whether a molecular structure would possess pharmacological properties, can be used to identify the relevant torsions in any given molecular structure. Characterizing conformers through the values of a set of torsions is not without precedent, and several approaches are based on this definition. For example, Torsiflex 10 is a software package that aims to explore a single molecule's potential energy surface utilizing a semirandom exploration of conformational spaces defined by torsions.