For the input features of the ligand-based (LB) model, we used a set of pose-independent molecular descriptors computed for each ligand using RDKit version 2019.09.1. These descriptors are conformation-independent and may be categorised as either (computed) experimental bulk properties (such as molar refractivity or logP) or theoretical descriptors derived from a symbolic representation of the molecule. The theoretical descriptors may be further categorised according to the dimensionality of the representation of the molecule from which they are derived. The conformer-independent descriptors we consider are either 1-D compositional properties (such as heavy atom counts, bonds counts, and molecular weight) or 2-D topological properties (such as fragment counts, topological polar surface area, and connectivity index). Any features with zero variance across the training data set, or that were null-valued (i.e. infinite or not computable) were excluded. We removed the Ipc index 29 as it produced extreme numerical values for larger molecules that were too large to be represented as 32-bit floats. This resulted in 185 ligand-based features, and the full list of features is given in the Supporting Information, under "RDKit Features".