We find that we can form clusters to estimate the P(active) value of untested building blocks. To do so, we first apply HDBSCAN to the UMAP coordinates of building blocks (Figure ), resulting in a set of clusters for each position in projected chemical space (Figure ). After assigning clusters, we compare the full width at half maximum (FWHM) of the distribution of P(active) values for HDBSCANgenerated clusters to randomly-generated clusters. We find that the average FWHM of the P(active) distributions from HDBSCANgenerated clusters is less than that for random clustering (Figure ), showing that compounds tend to be grouped into clusters of somewhat similar activity. Thus, we conclude that using a building block's cluster assignment to predict its P(active) value (Figure ) improves accuracy compared to random guessing.