Bio Graph

Bio Graph, developed by Causaly, is a biomedical knowledge graph platform designed to give R&D teams a complete and unbiased picture of the biomedical landscape. Built for discovery scientists, biologists, and translational researchers at leading biopharmaceutical enterprises, Bio Graph leverages cause-and-effect relationships to accelerate hypothesis generation, target identification, biomarker discovery, and preclinical safety research.

Thousands of scientists at world-leading biopharmaceutical organizations rely on Bio Graph to eliminate bias from decision-making, increase the success rates of new drug programs, and achieve up to 90% productivity gains throughout the preclinical research lifecycle.

Knowledge Graph Scale and Precision

• Contains 500 million facts combining generalized knowledge and biomedical topics
• Captures 70 million directional relationships between biomedical elements
• Supports 8 different relationship types — more than any other knowledge graph on the market
• Provides unbiased views of the research landscape at scale to unlock novel hypothesis generation

Exploration and Visualization Capabilities

• Navigable branching diagrams for exploring complex biological relationships
• Interactive network views to map connections across concepts
• Expandable timelines to track the evolution of research findings
• Natural language answers with inline citations for full verifiability
• Seamless user experience powered by Causaly's scientific AI copilot

Enterprise Data Fabric and Data Sources

• Surfaces side-by-side data visualizations drawing on both internal and external life sciences knowledge in seconds
• Continuously updated from millions of vetted scientific sources with alerts for relevant changes
• Integrates data from Medline, PubMed, and PMC
• Incorporates genome-wide association studies, patent filings, and clinicaltrials.gov
• Supports ingestion of internal organizational data via scalable pipelines

Scientific RAG Technology

• Causaly's proprietary Scientific RAG™ works in tandem with the knowledge graph
• Searches, retrieves, and ranks both internal and external data
• Ensures answers are relevant, accurate, and complete

Key Use Cases

• Biomarker discovery: Probe biological function, expression patterns, disease associations, and mechanism of action by asking questions directly in the scientific AI copilot
• Target identification and prioritization: Identify and prioritize therapeutically actionable targets using comprehensive cause-and-effect relationship mapping
• Disease pathophysiology: Explore and share knowledge about environmental and lifestyle mechanisms, anatomy, physiology, molecular processes, and disease heterogeneity
• Preclinical safety: Support preclinical teams with standardized, unbiased research insights across the R&D lifecycle

Bio Graph API

• Programmatically accessible via the Bio Graph API
• Enables data scientists, bioinformaticians, and computational biologists to integrate Bio Graph capabilities into in-house and third-party platforms and applications
• Extends the reach and power of existing internal tools

Causaly provides dedicated professional services support through a change management team comprising AI strategists and PhD scientists, partnering with customers from initial strategy and business alignment through deployment, program management, and ongoing day-to-day research support.