Developing a Specialized Dravet Syndrome Ontology for Rare Disease Informatics and AI Applications

Area of Science:

• Neuroscience and Bioinformatics
• Ontology Engineering
• Medical Informatics

Background:

• Dravet syndrome (DS) is a severe developmental and epileptic encephalopathy with complex, heterogeneous knowledge requirements.
• Existing epilepsy ontologies need specialized expansion to adequately represent DS-specific data domains.
• Integrating knowledge on seizures, development, behavior, genetics, and comorbidities is crucial for DS research.

Purpose of the Study:

• To develop a DS-focused ontology by specializing a pre-existing epilepsy ontology.
• To reorganize and expand DS knowledge representation across nine major domains.
• To create a foundational resource for data harmonization and AI-driven translational informatics in DS.

Main Methods:

• Expert-guided specialization of an epilepsy ontology using OWL.
• Scope expansion defined by a scientific advisory board and structured review meetings.
• Iterative ontology curation and assessment through downstream task-based reuse.

Main Results:

• A DS-focused ontology was created, reorganizing content across nine major domains.
• The ontology was expanded and made publicly available via BioPortal.
• The ontology facilitated two ontology-enabled LLM studies and an ongoing knowledge graph/AI assistant platform.

Conclusions:

• Disease-focused ontology specialization provides a durable infrastructure for DS data.
• The developed ontology enhances knowledge representation for Dravet syndrome.
• This resource supports AI-enabled translational informatics and research in DS.