Real-world insights from clinical literature to inform rare disease and cancer research
Genomenon’s Real-World Evidence for Precision Therapeutics leverages the company’s AI powered knowledge graph to extract real-world data (RWD) from scientific literature. This data is then curated by a team of over 100 expert scientists into actionable RWE datasets.
Get in touch with us to see how we can unlock RWE insights for your program.
Partner with us to: optimize clinical trial design, enhance diagnostic patient yield, and streamline regulatory submissions.
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How our technology finds patterns and correlations: ACMG Presentation
Here our VP of Technology Jonathan Eads breaks down how we used our Genomenon Genomic Graph (G3) to understand why colon cancer patients treated with immunotherapies exhibit a wide range of responses ranging from no effect to complete remission and if there are meaningful correlations.
How We Unlock RWE Insights
Genomenon uses its AI knowledge graph to mine over 10 million full-text scientific articles and 3 million supplementary data files to characterize patient data by its team of scientific experts. This comprehensive approach transforms previously inaccessible data into actionable insights, enabling refined disease-prevalence estimates, genotype-phenotype correlation discovery, and clarifying patient demographics and treatment outcomes.