Case Study: Queen’s University accelerates cancer research with Ontotext’s Target Discovery Platform

Queen’s University accelerates cancer research 500% faster with Ontotext

A research lab at Queen's University in Canada needed to expedite its cancer research by overcoming a strenuous manual process for validating over 2000 gene candidates, which took months to complete. To build a strong rationale for shortlisting genes, the lab turned to Ontotext and its AI-powered Target Discovery Platform.

Ontotext's solution integrated data from over 200 datasets and 80 million scientific articles into a knowledge graph, which normalized information and provided clear evidence for candidates. This allowed the researchers to discover insights 500% faster, reducing their research time from several months to just a few days. The platform also lowered the costs and risks of subsequent lab experiments for Queen’s University.

Queen’s University