The data acquisition and filtering steps are implemented as a Python script (pubchem retrieve.py) with a simple command-line user interface. The program allows downloading and filtering all the 60 MF-PCBA datasets, as well as any other PubChem assays with similar formats. The main arguments are --AID, indicating the AID of a PubChem assay corresponding to a SD experiment, --AID DR, optionally indicating the AID of a PubChem assay corresponding to a DR experiment that is separate from the SD dataset, --list of sd cols, indicating the names of the SD activity value columns (including replicates) as displayed on PubChem, --list of dr cols, indicating the names of the DR activity value columns, and transform dr, allowing the conversion to the corresponding pXC50 value. The GitHub repository contains customised scripts (i.e., with all the arguments already set) for all 60 MF-PCBA datasets, such that they can be simply downloaded and assembled with a single call to the intended script. Once downloaded and filtered, the DR datasets can be split into train, validation, and test sets according to the provided 5 random seeds, enabling easy comparison to the results obtained by previous work and in this paper. Splitting is demonstrated with an interactive notebook that is part of the source code.