To test the application, ShinyTPs was used to curate transformation reactions for 77 compounds from five different environmentally relevant datasets with information available from HSDB in the Metabolism and Metabolites section using the workflow shown in Figure . The full list of compounds is available in Table in the Supplementary Information. In total 582 chemical names were identified in the HSDB text entries in the Metabolism and Metabolites section. Out of those, 114 (~20%) corresponded to valid transformation reactions where the identified chemical name was either a TP or parent compound of the compound of interest. This demonstrates why manual validation of curated reactions is very important when handling text mined data, as there would otherwise be a significant number of incorrect reactions generated due to the presence of other chemical names in the text unrelated to transformation processes. A further 60 reactions containing chemicals that were not recognized by the text-mining tool were curated using the "adding missing entries" function based on expert knowledge. This highlights the need for not only approaches that have a higher accuracy and precision in recognizing chemical names, but also the development of approaches that are able to recognize complete chemical reactions. In combination, this further demonstrates the importance of manual review and curation in combination with the text mined entries to capture all the reactions described in the text.