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Repeated-dose toxicity (RDT) studies are one of the critical studies to assess chemical safety. There have been some studies attempting to predict RDT endpoints based on chemical substructures, but it remains very difficult to establish such a method, and a more detailed characterization of chemical compounds seems necessary. Cytochrome P450s (P450s) comprise multiple forms with different substrate specificities and play important roles in both the detoxification and metabolic activation of xenobiotics. In this study, we investigated possible use of P450 reactivity of chemical compounds to classify the compounds. A total of 148 compounds with available rat RDT test data were used as test compounds and subjected to inhibition assays against 18 human and rat P450s. Among the tested compounds, 82 compounds inhibited at least one P450 form. Hierarchical clustering analyses using the P450 inhibitory profiles divided the 82 compounds into nine groups, some of which showed characteristic chemical and biological properties. Principal component analyses of the P450 inhibition data in combination with the calculated chemical descriptors demonstrated that P450 inhibition data were plotted differently than most chemical descriptors in the loading plots. Finally, association analyses between P450 inhibition and RDT endpoints showed that some endpoints related to the liver, kidney and hematology were significantly associated with the inhibition of some P450s. Our present results suggest that the P450 reactivity profiles can be used as novel descriptors for characterizing chemical compounds for the investigation of the toxicity mechanism and/or the establishment of a toxicity prediction model.Inhibition of cytochrome P450s (P450s) by chemical compounds was investigated.Most of the compounds showed unique P450 inhibition profiles.The inhibition profiles can be used as novel descriptors to characterize chemicals.Associations were observed between inhibition profiles and repeated-dose toxicity endpoints.P450 inhibition profiles will help mechanistic study and prediction of toxicities.