A core aspect of the framework is its ability to employ a hierarchy of different approaches to compute a data set of physical properties, ranging from very rapid but less robust approaches such as evaluating surrogate models which have been trained on simulation data, to more robust approaches such as estimation by direct molecular simulation. Such a hierarchy enables the framework to automatically attempt to select the fastest approach which is able to estimate a given data set to within a user defined accuracy (Figure ). The framework employs a hierarchy of calculation approaches which currently includes estimation by direct simulation, and by reweighting cached simulation data. In the future, this may be extended to include both training of and estimation using surrogate models. b) Properties are cascaded through the calculation approaches, whereby those properties which could be estimated are returned, or those which couldn't be estimated with sufficient accuracy by this layer are moved to the next layer. This continues until either the full set of physical properties have been estimated using the specified force field parameters, or there are no more approaches left to attempt to estimate the set in which case the remaining properties are marked as unestimated and returned to the user.