Get a complete picture of the biomedical landscape
The most complete picture of the biomedical landscape
Unmatched scale with
500 million
facts combining generalized knowledge and biomedical topics
Deep understanding with
70 million
directional relationships between biomedical elements
Precise relationships with
8
different relationship types, more than any other knowledge graph on the market
"I’m amazed by the findings, and I love the graphical representation. I will find more things with Causaly than with my traditional, time-consuming search."
Accelerate, improve, connect, and standardize research across preclinical teams
Better decisions
Increase the success rates of new drug programs and eliminate weak ideas out of development pipelines by removing bias from decision-making.
For scientists, by scientists
Designed by scientists and used by thousands of scientists at world-leading biopharmaceutical enterprises and organizations.
Productivity gains
Discover hidden connections, form new hypotheses, and gain up to 90% more productivity throughout the preclinical research lifecycle.
How Bio Graph works
Bio Graph is about understanding the cause-and-effect relationships that are crucial to understanding disease biology. It leverages our high-precision knowledge graph to provide unbiased views of the research landscape at scale and unlock novel ways to generate hypotheses. Discovery scientists, biologists, and translational teams use Bio Graph to identify and prioritize therapeutically actionable targets, uncover biomarkers, and more.
Explore and visualize millions of concepts and relationships:
- Navigable branching diagrams
- Interactive network views
- Expandable timelines
Get answers in natural language, all verifiable with inline citations
Use a seamless, user-friendly experience via Causaly’s best-in-class scientific AI copilot
Current and comprehensive information
In seconds, users can surface side-by-side data visualizations that draw on life sciences knowledge both internal and external. Causaly’s sophisticated enterprise data fabric constantly updates information from millions of vetted scientific sources and alerts users of relevant changes. Data sources include:
- Medline, PubMed, and PMC
- Genome-wide association studies
- Patent filings
- clinicaltrials.gov
- Internal data via scalable pipelines
Next-level AI understanding
Working in tandem with the knowledge graph to ensure relevant, accurate and complete answers is Causaly’s proprietary search and retrieval technology: Scientific RAG ™ searches, retrieves, and ranks internal and external data.
Change management expertise at every stage
Causaly’s change management team spans AI strategists to PhD scientists who provide expertise at every step. They partner with customers throughout their journey: from strategy and business alignment, deployment, and program management, to day-to-day research support.
Causaly for R&D, AI, and IT teams
Causaly brings together millions of data sources, including preclinical, clinical, preprints, and customers’ internal information and makes it useful throughout the R&D process. Teams use Causaly to:
Identify and prioritize targets
With mature AI research tools and workflow automations built for target assessment, understand the complete picture of biomedical information in minutes and make stronger decisions about target prioritization.
Discover novel biomarkers
Probe the biological function, expression patterns, disease association, mechanism of action and more of a biomarker by simply asking questions in Causaly’s scientific AI copilot.
Decipher disease pathophysiology
Explore and share knowledge about environmental and lifestyle mechanisms, anatomy, physiology, molecular processes, heterogeneity, and more.
Bring the power of Bio Graph to internal platforms
Bio Graph is programmatically accessible via the Bio Graph API. Learn more about how data scientists, bioinformaticians, and computational biologists can use it to enhance the reach and power of in-house and third-party platforms and apps.
Learn moreGet to know Causaly
What would you ask the team behind life sciences’ most advanced AI? Request a demo and get to know Causaly.
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