Virtual Human Twin (VHT) Models for Cancer Research

Expected Outcome:Proposals under this topic should aim to deliver results that are directed and tailored towards and contribute to all of the following expected outcomes:Researchers of different disciplines use advanced multiscale Virtual Human Twins (VHTs) to expand the knowledge and understanding of cancer onset and progressionHealthcare professionals and researchers have access to advanced VHT-based solutions that model cancer onset and progression over time, contributing to improve personalised treatmentsResearchers, healthcare professionals, innovators and citizens have access to cancer VHTs through the UNCAN.eu and the advanced Virtual Human Twin platforms Scope:Virtual human twins (VHTs) are digital representations and in-silico models of an individual’s health and disease at different levels of the human anatomy (e.g. cells, tissues, organs or organ systems) for the prevention, prediction, screening, diagnosis and treatment of a disease, as well as the selection and personalisation of intervention options[1].The proposed topic will contribute to the EU Cancer Mission objectives by improving the accuracy of dynamic and multiscale VHTs to better understand cancer onset, predict progression and develop personalized treatments. Of particular interest for this topic are cancers with limited treatment options or unclear biological mechanisms, refractory cancers, rare cancers, early-onset cancers, cancer types with low five-year survival rates, or paediatric and adolescent cancers[2].Applicants should take advantage of technological advances in AI tools which open new opportunities to collect, combine and analyse large datasets of diverse types, including multi-omics patient data, tumour molecular profiles, immune profiles, medical images and real word data. Age, sex and gender differences should be duly considered. When relevant, proposals should build on current approaches, standards, data repositories and use modelling assets including but not limited to those p