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

CancerScan (Smart Pathology Slide Scanner for Diagnosis and Patient-Specific Treatment Recommendation in Oncology) is a research and innovation project funded under the European Innovation Council’s Horizon Europe programme. CancerScan aims to develop a smart pathology slide scanner capable of generating patient-specific tumour digital twins to simulate and evaluate treatment outcomes, empowering clinicians to make more accurate, personalised decisions in oncology care.

The project will combine advanced analysis of biopsy samples with clinical data to create a digital model of a patient’s tumour. This model will help simulate how different cancer drugs might work for that individual. CancerScan’s approach is built around five core elements: studying tumour cell communication, building biomedical knowledge graphs, analysing how these networks behave, modelling drug responses, and developing fast, integrated simulation hardware. Pancreatic cancer will be used as a model to examine how tumour environments affect treatment. Laboratory-grown tumour organoids will be matched with patient samples to ensure clinical relevance. The goal is to create a tool that supports better, more personalised treatment decisions.

The project duration is 36 months (from August 2025 to July 2028) and is coordinated by the Institute for Advanced Chemistry of Catalonia (IQAC) part of the Spanish National Research Council (CSIC). Partners include Vall d’Hebron Research Institute (Spain), Politecnico di Milano (Italy), Bielefeld University (Germany), Neovivum Technologies Doo Novi Sad (Serbia), Associação para a Investigação e Desenvolvimento de Ciências (Portugal), and MINDS & SPARKS GmbH (Austria). The consortium brings together top expertise in cancer research, artificial intelligence, modelling, and innovation—working together under strong ethical, gender, and open science principles.

For more information, follow the project website.

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