Dataset Preparation. To create our dataset, we used the KNIME Analytics Platform 4.6.5 to gather biological activity data from ChEMBL33. We obtained data for all available SLC6 members from various organisms, which initially amounted to 49867 data points. We then curated the data and standardized the molecules. In addition, we added 28 ligands to our dataset that were previously tested on the SLC6A19 transporter and were not included in the ChEMBL database. Dataset Curation and Standardization. The dataset curation steps were designed to produce a high-quality dataset suitable for regression modeling. Therefore, only data points with a standard_relation value of "=", standard_units of "nM", relationship_type of "D", and standard_type of "IC50" were considered. Only Homo sapiens, Mus musculus, and Rattus norvegicus were considered due to the abundance of available data on these organisms. Molecules were standardized using MolVS (version 0.1.1)(20) and RDKit (version 2022.09.1)(21) by sanitizing molecules, removing hydrogens, disconnecting metals, removing fragments, neutralizing charges, and removing stereochemistry. To maintain a homogeneous dataset, some molecules were removed for containing radioactive isotopes or silicon atoms. Additionally, data points were considered duplicates if they show identical standardized InChI codes, targets, and pchembl values and were thus eliminated.