Solubility is a critical property for pharmaceutical drug discovery, and problems with solubility can frustrate drug discovery efforts and block treatments. The bioavailability of a drug depends on the solubility difference between different crystal structures (polymorphs), dose, drug permeability, and formulation , so solubility plays a key role. Solubility problems can be unexpected and pose crucial obstacles that even threaten the administration of care. For example, a well-documented case occurred in the late 90's when ritonavir, an HIV-protease inhibitor marketed as Norvir, failed dissolution requirements . Since ritonavir is not bioavailable in its solid form, it was administrated in capsules containing solutions designed not to be saturated with respect to the originally known molecular crystal (form I) . The newly identified polymorph, form II, was unusually stable and unusually hard to crystallize; the preparation protocol of Norvir was inadequate to make capsules from the new polymorph, which severely threatened the supply of the drug in the market and endangered the lives of many HIV+ patients . Considerable effort has already been devoted to the methods to predict crystal polymorphs , but much less attention has been given to methods to predict solubilities, with or without likely polymorphs as input.