Bio Graph API

The Bio Graph API by Causaly is a powerful programmatic interface that gives data scientists and bioinformaticians direct computational access to the Causaly Knowledge Graph — one of the largest and most precise biomedical knowledge graphs available. Designed for R&D, AI, and IT teams in life sciences, the API enables rigorous, large-scale analyses that translate raw data into competitive knowledge and actionable insights, reducing evidence analysis timelines from months to hours.

By bringing the Causaly Knowledge Graph in-house, bioinformaticians can serve as stronger partners to scientists, delivering insights at scale and future-proofing drug development processes with high-quality, transparently sourced evidence.

Knowledge Graph Scale and Precision

• Over 500 million facts combining generalised knowledge and biomedical topics
• 70 million directional relationships between biomedical elements
• 8 distinct relationship types — more than any other knowledge graph on the market
• Unique insights into causality, not just co-occurrence
• Precise and verifiable results with a strong signal-to-noise ratio

Key Capabilities and Access

• Simple API token-based authentication for straightforward integration
• Pre-made templates and dedicated R and Python libraries to accelerate development
• Access to 250,000 UMLS concepts for standardised biomedical terminology
• Retrieve relationships for 1,000+ target-disease pairs in fewer than 10 minutes
• Saves thousands of hours per year in knowledge aggregation, comprehension, and document and evidence analysis

Target Identification and Prioritisation

• Rapidly identify novel or promising target-disease relationships at scale
• Prioritise targets using multiple dimensions including strength of evidence, direction of regulation, and levels of validation
• Supports mature AI research tools and workflow automations built for target assessment
• Enables a complete picture of biomedical information to support stronger decision-making

Risk Assessment and Toxicology

• Expedite the design of safety assessments and toxicology experiments
• Query which organ system classes are affected by a set of genes
• Determine what cellular and tissue functions are impacted by gene inhibition
• Assess the effects of genes identified through knockout or knockdown studies

Biomarker Discovery

• Access hundreds of millions of data points in minutes to generate a landscape view of genes, proteins, and functions implicated in a disease
• Identify diagnostic biomarkers for specific diseases
• Determine gene or protein expression patterns that predict therapy response
• Compare strength of evidence across multiple biomarker candidates
• Navigate a multi-dimensional web of text and visuals to explore the knowledge landscape

Data Pipeline Enrichment

• Integrate the Bio Graph API into internal data pipelines to add high-quality evidence dimensions
• Qualify the scientific rationale and strength of evidence for drug development decisions
• Identify other diseases targeted by a given drug and assess the strength of supporting evidence
• Surface relevant literature to evaluate likelihood and potential of a given hypothesis

Broader R&D Applications

• Supports deciphering disease pathophysiology, including environmental and lifestyle mechanisms, anatomy, physiology, molecular processes, and disease heterogeneity
• Integrates preclinical, clinical, preprint, and customers' internal information sources
• Applicable across R&D, AI, and IT teams throughout the drug development process

The Bio Graph API is built to integrate seamlessly into existing scientific workflows, supporting teams through pre-made templates and language-specific libraries for R and Python. It draws on both external published literature and customers' internal data, making it a flexible and scalable solution for life sciences organisations seeking to accelerate and strengthen evidence-based decision-making.