We consider a VS setting to evaluate the implications of RL and AL methods from an oraclecall efficiency (novel hits per oracle call) perspective. We begin by sampling 100 000 molecules from the REINVENT prior, which is trained to mimic the ChEMBL database, and evaluating the complete library with two distinct computational models/oracles (Methods): 1) a shape and color pharmacophore query for Cyclooxygenase-2 (COX2) (PDB ID: 1CX2) based on the native SC-558 ligand implemented using ROCs 2) a docking protocol for the Retinoic Acid Receptor Alpha (RXRα) (PDB ID: 7B88) , implemented using AutoDock-Vina We judge hits for each oracle based on having a greater predicted affinity than obtained for their respective native ligands (0.6 for ROCs and -11.4 kcal mol -1 for the docking oracle respectively). With exhaustive screening of the library, we identify 30 unique Murcko scaffolds and 41 unique hit SMILES for ROCS (364 and 369 for docking), for a hit rate or oracle-call-efficiency of 0.03% / 0.04% (0.36% / 0.37% for docking).