Integrated precision medicine for rational cancer decisions
A patented proprietary approach to personalized cancer care
We've developed a proprietary, AI-ready database built from unique tumor signatures, enabling a new level of precision in oncology.
Unlike conventional approaches that rely on generalized reference profiles, our method compares each tumor to the biological baseline of the patient's own organ. This individualized comparison captures subtle, patient-specific variations that standard models miss.
As a result, our approach aims to predict treatment response more precisely, paving the way for more effective, personalized therapies for every patient.
Step 1
Analysis
Proteomic analysis of the patient’s tumor and micro-environment profile defines the tumor’s specific signature.
Step 2
Proprietary database
Specific tumor signatures from patient cohorts are collected and paired with their observed treatment response, building a foundational dataset that correlates hundreds of profiles to therapy effectiveness.
Step 3
AI-Powered prediction
BeLiver’s AI model is trained on this database to understand the complex patterns of treatment response. For a new patient, the model analyzes their signature to predict a treatment response likelihood.
Why focusing on the proteome ?
Proteins, not genes, drive disease biology. Unlike DNA or RNA readouts, proteomics captures the active molecules that reflect real-time cellular function after genetic and regulatory layers have taken effect.
Because proteins execute cell programs and are the primary drug targets, the proteome is the closest layer to pathology and therapeutic action.
By measuring protein expression and signaling pathway activity, we aim to reveal mechanisms that shape treatment response, providing deeper insight and supporting more precise approaches.
A proof-of-concept study in liver cancer
Our initial proof-of-concept studies, conducted on over 80 liver cancer patients, showed promising ability to distinguish responders from non-responders to major systemic therapies including both first- and second-line treatments.
Building on these encouraging results, we are now expanding our clinical validation through partnerships with seven leading French hospitals, with the goal of evaluating our test's potential to support first-line treatment selection and contribute to improved patient outcomes.
A platform designed to be scalable across multiple cancers
Our platform has already shown promising results beyond liver cancer, with early explorations in other cancer types where reliable biomarkers are lacking and prognosis remains poor.
By leveraging deep biological profiling and AI-driven insights, the platform is designed to adapt to diverse tumor complexities, enabling personalized treatment decisions across a broad spectrum of cancers.
This scalability potential positions us to contribute to oncology care on a larger scale, addressing urgent unmet needs and potentially improving outcomes for many more patients worldwide.
Team Publications
Discover the science powering our unique technology.
Proteomic profiling of advanced hepatocellular carcinoma identifies predictive signatures of response to treatments
Delamarre et al.
Spatial characterization of β-catenin-mutated hepatocellular adenoma subtypes by proteomic profiling of the tumor rim
Sylvaine Di Tommaso, Cyril Dourthe, et al.
Proteomic Profiling of Hepatocellular Adenomas Paves the Way to Diagnostic and Prognostic Approaches
Dourthe C, et al.
ASS1 Overexpression: A Hallmark of Sonic Hedgehog Hepatocellular Adenomas; Recommendations for Clinical Practice
Sala M, et al.
Argininosuccinate synthase 1 (ASS1): A marker of unclassified hepatocellular adenoma and high bleeding risk
Henriet E, et al.
BeLiver's services are currently under development and are not yet commercially available. They have not received regulatory clearance (CE marking under IVDR in Europe). The information on this website describes our research and development activities and does not constitute a commercial offer or medical advice.
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