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Project Summary

CancerScan - Smart pathology slide scanner for diagnosis and patient-specific treatment recommendation in oncology

CancerScan aims to develop a smart digital slide scanner capable of generating patient-specific tumour digital twins to simulate drug responses. Focusing on pancreatic cancer, it integrates multi-omics data from biopsies with clinical information to understand how the tumour microenvironment influences treatment outcomes. By combining lab-grown tumour models with clinical validation, CancerScan will support more precise and personalised cancer treatment decisions, helping clinicians identify the most effective therapy for each patient.

Project Objectives

MAP

the influence of the tumour microenvironment (TME) on the efficacy of chemotherapeutic treatments.

DEVELOP

a standardised knowledge graph that integrates experimental, public, and ontological data to represent the TME’s influence on drug efficacy.

LEARN

the proto-grammar of tumour communication identifying structural properties and implementing statistical pattern analysis and machine learning.

DESIGN & VALIDATE

a platform for the automated generation of tumour digital twins for specific tumour scenarios.

CREATE

an embedded hardware/ software system for automating the creation of tumour digital twins from digital slides and getting simulation results.

BOOST

awareness of the project outcomes through communication and dissemination activities and engage main target groups.

Project Consortium