Accelerating Cancer Research with AI-Powered Target Discovery
Using Graphwise's GraphDB and the Linked Life Data Inventory, a Queen's University research lab accelerated cancer research by streamlining candidate validation from months to days, discovering insights faster and enabling high-confidence target prioritization with minimal technical expertise.
The Client
Research lab at Queen's University in Canada focused on expediting analysis of receptor tyrosine kinase (RET) in cancer research
The Challenge
The lab faced a massive backlog of 2000+ targets from genome-wide screens requiring a laborious, months-long manual validation process
The Solution
Using Graphwise's GraphDB and the Linked Life Data Inventory, the lab streamlined candidate validation and prioritization through AI-powered analysis of 200+ datasets and 80+ Mio scientific articles
Technical capabilities
Streamlined 2000+ targets using AI-driven Target Prioritization
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Unified 200+ datasets and 80+ Mio scientific publications into a knowledge graph
Business outcomes
Reduced validation and research timelines from months to days through a 500% faster insight discovery
Increased confidence in target selection with explainable, traceable results
The Challenge
A Queen’s University research lab wanted to expedite their analysis of how receptor tyrosine kinase (RET) mediated different processes in cancer. The lab used genome-wide large screens to identify candidates for validation, but the process was strenuous and time-intensive.
The main challenge was building strong rationales for shortlisting candidates among thousands of genes. Manual candidate validation required screening gene properties across different genomic databases, pathways, interactions, and literature to provide solid evidence for each candidate.This created a huge backlog of 2000+ targets requiring validation. The team shared that this manual process would take several months to complete.
The Solution
The lab implemented Graphwise’s GraphDB and the Linked Life Data Inventory solution to streamline candidate validation and prioritization. It uses LinkedLifeData Inventory with over 200 integration-ready datasets maintained in a unified knowledge graph. This provides quick, efficient access to information while linking facts to create an enriched network of knowledge.
The solution normalizes data from over 80+ Mio scientific articles, publications, patents, and clinical trials. AI models automatically extract relevant information and integrate it into the knowledge graph, putting derived facts into context with structured data for clear evidence and provenance.
This enabled researchers to shortlist high-potential genes and build strong rationales for pursuing them with comprehensive data integration.
The Impact
Graphwise’s GraphDB and the LLDI delivered transformative results:
Accelerated research timelines reducing validation from several months to just days, with researchers getting actionable results within a couple of days of setup
AI-driven large-scale prioritization unlocking new thinking patterns and enabling identification of previously unavailable insights into gene properties
Increased confidence in candidates through clear explainability and traceability, allowing hypothesis building based on solid evidence rather than “black box” results
Today, these have become an integral part of the lab’s workflow, enabling researchers to leverage complex biomedical relationships and gain meaningful insights without requiring technical programming skills.
“When I think of Graphwise’s solution, I believe it would be an integral part of every workflow. Now I always keep an open tab while I’m doing my work and it’s a super useful tool.”
Montdher Hussain, Mulligan Lab AT Queen’s University
Struggling with massive datasets requiring months of manual validation?
Whether you're an academic research lab, pharmaceutical company, biotech firm, or life sciences organization, Graphwise can help you:
Accelerate research timelines from months to days through AI-powered analysis
Unlock new insights by integrating 200+ datasets and millions of scientific articles
Enable high-confidence decision-making with explainable, traceable results