Towards the development of a FAIR-compliant biomedical ontology for colorectal cancer

Despite the widespread development of ontologies in many domains of healthcare, the field of colorectal cancer (CRC) presents a notable gap considering the lack of standardized data models tailored to the CRC domain. To address this gap, we developed a structured, systematic approach to model CRC-related data. A reference data model (RDM) was first defined, including 250 terminologies related to sociodemographics, clinical biology, lifestyle, symptoms, among others. Each terminology was linked with globally recognized HL7 standards, including SNOMED-CT, LOINC, and ICD-10/11, among others, fulfilling the principles of findability, accessibility, interoperability, and reusability (FAIR) to facilitate its integration into global healthcare systems. The RDM was then transformed into an ontology using Protégé. The resulting ontology presents a unified framework for CRC data, enhancing data consistency across various healthcare platforms and research studies. The ontology's availability on GitHub invites global collaboration, ensuring its continual evolution and relevance in the rapidly advancing landscape of healthcare. The proposed standardized, accessible, and comprehensive data model has the potential to significantly impact CRC research and treatment, paving the way for more effective, personalized patient care and fostering a collaborative environment for ongoing advancements in the field.