For each active learning experiment, 64 molecules were selected from the screening library. These molecules are then removed from the library. Every set starts with a random hit molecule, after which the remaining molecules are randomly sampled using a uniform distribution. Until the budget of 1,000 molecules was depleted, a model 𝑀 was trained on the training set, after which bioactivity predictions were made on the screening library. Using one of five acquisition methods (see Acquisition methods), 𝑛 molecules are labelled and moved to the training set.