Industry
Healthcare & Life Sciences
The integration and analysis of diverse datasets is key to unraveling the complex relationships between
genes, diseases, and pharmaceuticals. In this white paper, we have developed a comprehensive knowledge graph
by merging gene data from the National Center for Biotechnology Information (NCBI), disease data from
DisGeNET, and drug data from DrugCentral. This knowledge graph visually captures the intricate
interconnections among these entities. Additionally, we leverage spaCy’s Named Entity Recognition (NER)
model to identify key medical entities, including diseases, genes, drugs, and symptoms. This approach aims
to:
- Revolutionize drug discovery and repurposing by utilizing structured data and knowledge graphs
- Develop a method to streamline the drug discovery process, reducing costs by 50% and accelerating the process tenfold
- Empower researchers to uncover complex relationships between genes, diseases, symptoms, cellular functions, mechanisms of action, and drugs, enabling more efficient and impactful decision-making
