New functional forms can be implemented through the OpenFF-SMIRNOFF plugin code, which integrates seamlessly with the OpenFF infrastructure. The plugin and the Evaluator framework may enable one to build a next-generation implicit solvent model from the ground up and fit them to physical properties rather than to finite difference PB energies as previously done. More broadly, although the work presented here showcases the optimization of an implicit solvent model with the OpenFF-Evaluator framework, the same general procedure can be applied to other potential functions and force field components. For example, it would be of interest to reoptimize Sage's LJ parameters, in the context of an explicit solvent model, against a dataset comprising the original reference data used for Sage and supplemented by host-guest binding data. This will be more computationally demanding than the present study, but should be well within reach of current computing resources. This will add another restraint to the optimization, and the inclusion of host-guest binding affinities to the optimization may improve the ability of future force fields to accurately predict protein-ligand binding affinities.