Find the most recent publications of Renovaro’s core scientifical team

White Paper


Among different modalities for the early detection of cancer, cell-free DNA (cfDNA) extracted via minimally invasive liquid biopsies has emerged as a promising biomarker. As it provides a molecular snapshot of the patient, it is being investigated as a pan-cancer detection biomarker (1).

However, current methods still lack sufficient sensitivity for early detection of cancer (2–4).
RenovaroCube (“The Cube”) is an AI platform designed to accelerate cancer diagnostics. It is our firm belief that no single model or modality will reach the requisite sensitivity to detect cancer early.

Therefore, The Cube integrates multi-omic data, offering a uniquely comprehensive approach to cancer detection by leveraging a library of trained models for multiple omic
layers. Here, one such underlying model is presented, focusing on the detection of cancer from cfDNA sequencing data using fragmentomics.

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