Within this context, Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) is a series of blind challenges that bring together scientists on a global scale to improve the capability of current computational methods in drug discovery. This collaborative approach aims to better facilitate development of the next-generation computational models than can be used as predictive tools in drug discovery. Various iterations of SAMPL over the last decade have focused on evaluating how well physical and empirical modeling methodologies can predict several physicochemical properties of drugs that can be used to aid in drug discovery, such as hydration free energies, acid dissociation, and partition and distribution coefficients .