Cheminformatics may be used for substance grouping based on predictive models for properties such as biodegradability, mobility, and toxicity. PubChemLite predictions suggest that 41% of potentially environmentally relevant compounds would be considered mobile (147,930 compounds) and 21% would be considered very mobile . Certain compound classes, such as triazines, aromatic amines, triazoles and PFAS, are likely to be persistent, nonbiodegradable, and toxic. As shown in Table , the numbers are high and restricting these compounds as a group would be challenging; however, prioritizing members of these large groups for property testing is warranted as they contain a substructure associated with a PMT/vPvM substance group. Additional strategies are needed to prioritize some substances for regulation, such as mapping the uses of these chemicals and exposure which requires more data availability following FAIR principles. Some strategies proposed for the prioritization of substances for testing or assessment of PMT/vPvM include (i) better understanding and the use of exposure/ emissions information such as Occupational Exposure Banding and environmental exposure to the PMT/vPvM substances, (ii) the use of in vitro, in vivo and in silico techniques to generate relevant toxicological data that will support prioritization, identification and regulation of PMT/vPvM substances. These strategies in combination with substance grouping could result in substituting PMT/vPvM substances with safer alternatives.