In comparison, we used the average computation times reported by Yang et al. to approximate the time required to set up an active learning workflow for 4.8 billion molecules. This previous study docked 0.1% of the library at each round of active learning at an average speed of 1 second per molecule per CPU core with DOCK (or 7.9 s with Glide). This previous study also reported a 16-hour ML training time, which we assumed was constant irrespective of the total library size, and a 5ms per molecule per CPU core ML prediction time. We modeled the DOCK calculations and ML predictions as scaling linearly with the number of cores and predicted the total time required to do initial docking, training, and ML prediction for two rounds of active learning, as investigated in the previous study.