One of the avenues that focuses on this idea are the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges, which are an efficient way to identify and analyze new computational approaches for drug discovery through predicting various properties associated with pharmaceutical chemistry such as host-guest binding, protein-ligand interactions, and thermodynamic properties, e.g., pKa, and logP. These blind challenges remove methodological choices that may bias the results, and thus would overcorrect the true predictive ability of a computational method. In the ninth iteration, the challenge was issued into multiple parts including host-guest challenges, a protein-ligand challenge on nanoluciferase, and a toluene-water logP (logPtol/w) challenge.