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Accelerating Cancer Research with AI-Powered Target Discovery

Using Target Discovery, 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  Using Target Discovery, the lab streamlined candidate validation and prioritization through AI-powered analysis of 200+ datasets and 80+ Mio scientific articles

The Solution

Using Target Discovery, 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  =
  • 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 Target Discovery 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

The Target Discovery solution 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, Target Discovery has 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 Target Discovery, 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
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Details

Solution: Target Discovery
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Facing Similar Challenges?

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

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