The dataset for the molecular optimisation task consists of a set of matched molecular pairs (MMPs) extracted from ChEMBL , together with the property changes of the MMPs. Three molecular properties: logD, solubility and clearance, are optimised simultaneously. Property values for each molecule were predicted from models built using internal, experimental data. The property prediction models were used for both the construction of training data, and also for the evaluation of the generated molecules during testing. The dataset includes 160,831 train, 17,871 validation and 19,856 test MMPs. Full details of the dataset and the models used to generate molecular property predictions can be found in .