Our calculations were kept rather short for computational efficiency, resulting in somewhat high statistical errors. For computational efficiency, we ran only 1 ns per lambda value, allowing each k B T log γ ∞ to be computed quite quickly. With additional sampling at each lambda value we could further reduce the statistical error and better ensure that sampling is adequate, so extending the simulations may be something to explore in future work. Advances in hardware have already provided considerable gains in this area, already making it possible to perform the large number of calculations reported here in a relatively short amount of time, in part due to the availability of GPUs. Each calculated k B T log γ ∞ value requires two solvation free energy calculations, which modestly increases the computational cost in comparison to our traditional approach of using hydration free energies, which requires a single free energy calculation . This small increase is worthwhile given that hydration free energies involve gas-to-water transfers while many events computational chemistry seeks to predict (e.g. binding, solubility, partitioning, permeation, etc.) involve transfer between condensed phases. Thus IDACs may be particularly appealing for force field parameterization since IDAC calculations involve the transfer of molecules between condensed phases, similar to biological and pharmacological events which typically involve transfer from one condensed phase environment to another.