To visualize the chemical space coverage of generated compounds we compute a UMAP (Uniform Manifold Approximation and Projection) , for all hit scaffolds, using a UMAP model trained on the REINVENT prior (Supporting Figure ). We show that the sampling space is reduced in the RL-AL MPO conditions relative to RL-baseline in the ADV condition, however, we see a compensatory uptick in the sampling of compounds with enriched MPO scores. For ROCS we observe that the MPO strategy both increases the MPO score, and distribution of hits compared to baseline.