Connect targets and diseases with confidence,
in seconds
Quickly find the right target-disease connections so your team can focus on science, not search.
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The high-stakes science of getting targets right
Selecting the right biological targets is a high-stakes decision that can define the success of a therapeutic program. But finding truly disease-relevant targets is incredibly complex. Smarter target selection is about making those connections faster and with greater clarity and confidence. It means linking genes, proteins, or pathways to diseases based on high-quality, contextualized evidence.
When done right, it unlocks therapeutic opportunities with real clinical potential. But the path to confident decisions is often blocked by data fragmentation and research silos.
The challenge: volume, complexity, and noise
Life Sciences R&D teams face a mountain of disconnected data. Genetic studies, omics data, and clinical observations are scattered across siloed systems (both internal and external), publications, and formats.
Manual methods drain resources and extend timelines. Researchers spend hours combing through biomedical papers, research reports, experimental data, and databases, only to end up with incomplete or biased analyses. Parsing that volume manually isn’t just slow, it’s risky: without a clear way to evaluate evidence, promising targets get overlooked, and weak associations can get prioritized.
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A more confident path to therapeutic discovery
Causaly transforms how researchers discover and validate target-disease associations. Our platform combines a biomedical knowledge graph with AI-powered discovery tools to surface high-confidence connections in seconds. With Causaly, R&D teams can:
Uncover hidden target-disease connections buried in scientific literature, experimental data, and databases.
Accurately assess the strength of evidence.
Integrate external and internal data into a unified view, andAs a result, they can prioritize targets more effectively and reduce the risk of costly failures.
Connect the dots across vast biomedical evidence
Our AI platform interprets millions of scientific documents ( spanning literature, trials, mechanistic studies and more), to reveal hidden links between drugs, targets, and diseases.
Surface context-rich, high-quality insights
Causaly doesn’t just show associations. It shows why they matter. It brings together mechanistic rationale, strength of evidence, and source data in one intuitive interface.
Accelerate hypothesis generation
Explore biological pathways, test ideas, and validate target-disease relationships in minutes, not weeks.
Reduce risk. Prioritize with confidence.
Confidently rule in (or out) new opportunities based on high-quality, contextualized evidence. De-risk your pipeline and focus on programs with real clinical potential.
Faster answers and deeper insights
“Causaly is my go-to tool for researching drug-disease associations because it is an easy way to look for relevant publications. The quality of the results is better because I see diseases and not documents; I think the relevance of the articles is much higher in Causaly vs the others and I can even refine the searches through the filters.”
Senior Medical Information Analyst
“One of the most valuable things about Causaly is that it doesn't cost you time in the lab. You can find something on the platform and look at the experiments performed; what are the methods used, can they be reproduced, do you agree with the results. This helps with understanding what validation experiments to conduct.”
Data Science Specialist
“As soon as I started using Causaly, I immediately realized its benefits. It helps me a lot in my day-to-day work interpreting a range of data and understanding connections with the disease, and I find myself always coming back to Causaly.”
TranslationalResearch Scientist
Proven productivity benefits to life science organizations
77%
Of scientists believe that Causaly improves their decision-making.
(Source: Causaly customer survey.)
40%
Average time savings observed.
(Source: Causaly customer survey.)
$26-42M
Potential cost savings to be realized
(through efficiency gains across a typical organization of 5,000+ scientists; and faster deprioritizing non-viable targets.)
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Standardize and automate with hyper-efficient, intelligent research tools
Generative AI Copilot
Ask questions in simple, natural-language and obtain robust, cited answers on causal relationships, relevance, and more from internal and external data.
Enterprise Data Fabric
Stay on top of a research area with customizable alerts that notify users the moment new information appears or existing information changes.
Knowledge Graph
Organize facts and relationship triplets across hundreds of semantic categories with the largest, high-precision knowledge graph for scientists.
Team Workspace
Collaborate across multidisciplinary teams and easily share novel findings, data, and resources to create a holistic view of disease mechanisms.
Get to know Causaly
What would you ask the team behind life sciences’ most advanced AI? Request a demo and get to know Causaly.
Request a demo