Targeted treatment for better outcomes

Precision oncotherapy combines histological, proteomic, and imaging data to select optimal therapies based on individual tumor characteristics and patient biology. Our AI predicts treatment response, potential side effects, and recurrence risk before therapy begins.

This personalized approach maximizes treatment efficacy while minimizing unnecessary interventions and adverse effects.

What makes it work

Module 3 uses advanced modeling and multi-omics analysis to create individualized treatment plans that adapt to each patient's unique biology.

• Transformer + GNN + topological deep learning models

• Integration of 3D tumor structures via neural fields

• Recurrence and side-effect prediction

• Physician interface with explainable recommendations

Innovative Extensions

We're pioneering research into proteomic data from Olink-like panels (250+ proteins) to identify biomarkers before clinical manifestation. Our experimental work with nanomaterials (MXenes) explores next-generation diagnostics and targeted therapy delivery.

MXenes can be functionalized for protein and biomarker detection, photothermal therapy, ultrasound therapy, and multifunctional agent delivery—enabling innovative treatment scenarios beyond current standards of care.

Interoperability

Module 3 aligns with Cancer Image Europe and UNCAN.eu standards, supporting collaborative model validation across EIC portfolio projects. The platform maintains compatibility with international healthcare systems and regulatory frameworks.