We develop biomarkers that capture complex cancer biology from gene expression data, transforming raw RNA-seq data into actionable insights with predictive AI. Our mission is to help partners understand how their molecule works, and just as importantly, when it doesn’t.

A New Approach to Biomarkers
We see biomarkers as more than just diagnostic tests, they are measurable characteristics of health or disease, unlocking key insights into drug mechanisms, patient responses, and treatment durability. Whether delivered as an algorithm, an interactive tool, or a regulatory-ready software package, their true value lies in the answers they provide.

Why RNA-seq?
RNA-seq offers a highly multidimensional, phenotypic view of tumor biology, capturing more detail than DNA alone. It’s commoditized, reliable, and cost-efficient, making it an ideal tool for precision medicine.

The Genialis Supermodel is a large molecular model trained on a vast set of globally diverse RNA sequencing data. 

The Supermodel deciphers the underlying biologies of cancer, revealing critical states and processes. By minimizing bias and transforming thousands of data points into concise, signature-based scores, it supports the creation of biomarker algorithms. These algorithms help categorize patients, predict responses to specific treatments, and guide more informed decisions for non-responders.