Chemotherapies follow well defined standard regimen (or protocols) recommended by scientific societies. Those are organized in cycles during which cytotoxic molecules, doses and days of administration are precisely specified. But in real life, treatment may not go as planned. Toxicity events, holidays and other factors lead to changes in doses and delay of administration, what may impact the effect of the treatment. Modeling both protocols and their real-word implementation in a unique framework would facilitate further comparisons.To this aim, we propose an ontology named ChemoOnto to represent both protocols and treatment courses. ChemoOnto, provides 10 classes, 16 object properties and 24 data properties to model the complexity of chemotherapy and cover both standards and administered courses. ChemoOnto reuses several domain ontologies, particularly the Time Ontology and a drug knowledge graph named Romedi. We instantiated ChemoOnto with 1973 chemotherapy protocols and treatment data of 3,923 patients. We added toxicity events detected in a previous work to our knowledge graph and applied temporal reasoning using SWRL rules to detect toxicity events occurring during patient’s chemotherapies.ChemoOnto is an original model that may support various applications to understand and analyze chemotherapy courses and response, by considering the complexity of their description.