To recognize the PAINS, present in compound libraries, several computational tools, and AI methodologies have been developed to filter, remove, or eliminate these artifacts to avoid their effects on pharmacological trials and molecular modeling studies . However, the structural fragments present in these promiscuous compounds have shown variable biological activities in biological tests . Platforms based on substructure filters have been commonly used to identify and eliminate these interfering compounds . Some platforms used are: AlphaScreen technology [139, 140], and PrePeP . In addition, in-house methodologies have been developed for certain PAINS with the KNIME [142] software, the OpenEye [143] chemoinformatics tools, and the R and RStudio applications, which use the Java and R programming languages .