Real-World Evidence for Precision Therapeutics

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.

Interested in learning how?

RWE in Action: Case Studies

Read our case studies to see how we’ve supported clients by delivering RWE insights on disease prevalence, inclusion criteria, clinical biomarker and patient stratification.

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RWE for Precision Therapeutics: Informational Sheet

This overview explains Genomenon’s unique approach in extracting RWD from clinical literature through our AI and team of experts and the kinds of insights we can provide.

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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.

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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.