| Date & Time | 16-18 March 2027 |
|---|---|
| Location | Bergamo, Italy |
Computational models are becoming part of how cancer is studied, alongside laboratory and clinical work. AI methods, including foundation/generative models, are starting to capture aspects of the molecular and spatial organisation of tumours from large, multimodal datasets. Efforts to simulate how tumours respond to perturbation and to predict individual patient outcomes are active but harder, and results haven’t yet been shown to hold at the scale and reliability that clinical use requires. Validation, generalisation across cohorts, interpretability, and integration with experiments and trials remain open problems.
This conference will bring together computational and experimental scientists and clinicians to assess what current models can and cannot do, where they add value in discovery and care, and what’s needed to move from representation toward reliable simulation and prediction. The goal is a realistic account of where these approaches help, where they fall short, and what comes next.
The target audience for this conference is basic, computational, and translational cancer scientists, clinicians, and machine learning researchers, both senior and early career, from academia and industry, who want a broad overview of computational modelling, AI, and virtual systems in cancer biology and their translation to the clinic.
Deadlines:
- Travel Grant application deadline: 18 January 2027
- Abstract submission deadline: 18 January 2027
- Registration deadline: 15 February 2027
