DISGENET

DISGENET, developed by MedBioinformatics, is the world's most reliable and extensive gene-disease association database, established in 2010 and built on over 15 years of life science expertise. It is designed for drug discovery researchers, bioinformaticians, clinical researchers, and precision medicine teams who need immediate access to comprehensive, high-quality disease genomics data. With information equivalent to reading over 30 million articles, DISGENET provides a powerful foundation for accelerating drug R&D, identifying validated drug targets, and unlocking new precision medicine possibilities.

MedBioinformatics, the company behind DISGENET, offers a broader suite of AI, knowledge graph, and NLP solutions that help life science organisations transform complex biological and textual data into actionable insights. Their mission centres on enabling safer and more sustainable product development while prioritising human health and well-being.

DISGENET Database Highlights

• Contains over 38,000 disease associations, making it the most extensive gene-disease knowledge platform available
• Has accumulated more than 8,200 citations worldwide, reflecting its widespread adoption in the research community
• Achieves a 92% NLP F-score, demonstrating the high accuracy of its text-mining and natural language processing capabilities
• Provides data comparable to having read over 30 million biomedical articles, giving researchers immediate access to the latest and most relevant disease genomics information
• Supports identification of drug targets with proven links to disease mechanisms, which has been shown to significantly increase the probability of clinical trial success
• Enables researchers to find variants causing rare diseases, with a large and well-structured database that simplifies evidence retrieval and presentation
• Supports investigation of protein misfolding, DNA methylation, and other complex disease pathology mechanisms

Natural Language Processing Capabilities

• State-of-the-art NLP solutions make textual data searchable, analysable, and actionable
• Unlocks insights hidden within unstructured biomedical text, including the vast volume of papers entering PubMed each year
• Accelerates informed innovation by extracting and structuring knowledge from scientific literature at scale
• Applied to anticipate drug toxicity and support data-driven drug safety assessments
• Used to process and standardise preclinical toxicology data, including dense tables, semi-structured datasets, and long-form PDF reports, in alignment with regulatory standards such as SEND (Standard for Exchange of Nonclinical Data)

AI and Knowledge Graph Solutions

• Reveals insights from complex biological networks through fine-grained, comprehensive coverage of relationships between biomolecules
• Enables semantic integration of heterogeneous life science data sources
• Supports drug target identification and validation using human genetics evidence
• Facilitates genetics-based drug and chemical risk assessment, addressing regulatory requirements such as the Frank R. Lautenberg Chemical Safety for the 21st Century Act
• Provides data analytics capabilities to help organisations develop innovative and safer products

Key Use Cases and Applications

• Drug discovery and development: leveraging genetic evidence to identify and validate drug targets, improving the probability of clinical success
• Rare disease research: searching for disease-causing variants and finding supporting evidence efficiently
• Precision medicine: uncovering gene-disease associations to enable more targeted therapeutic strategies
• Drug safety and toxicology: anticipating adverse effects and supporting regulatory-aligned preclinical data workflows
• Chemical risk assessment: incorporating human population variability into health risk evaluations for new and existing chemicals

Access and Licensing

• Academic and not-for-profit researchers can access DISGENET's core biomedical data at no cost through an academic licence
• Additional options utilising advanced NLP technology are available for deeper insights
• The platform is available as a unified web platform at disgenet.com, consolidating previously separate offerings into a single resource
• Over 100,000 web users rely on DISGENET for their research needs

MedBioinformatics is an active participant in collaborative research initiatives, including the IHI JU VICT3R initiative, a public-private partnership aimed at transforming nonclinical drug and chemical safety evaluation and reducing the number of animals used in experimental studies. The company continues to expand DISGENET's capabilities and its broader portfolio of NLP and AI solutions to support the life science community in building safer, more effective products.