The proposals should address all of the following activities:

• Develop multi-scale and multi-organ, dynamic, interoperable, modular computational models, capable of accurately simulating the individual patient patho-physiology, spanning different anatomical scales, from the molecular to cell, tissue, organ and systems level, as necessary. Proposals should be multidisciplinary and focus on groups of communicable and/or non-communicable diseases with commonalities within the same or across different medical domains, including co-morbidities. SME(s) participation is encouraged with the aim to strengthen the scientific and technological basis of SME(s) and valorise their innovations towards citizen and patient benefit.
• Advance the state of the art in multi-scale modelling by employing diverse modelling methodologies, including but not limited to: mechanistic modelling, artificial intelligence, agent-based and network physiology as a means for modelling the healthy state, disease onset, progression, treatment and recovery. Availability of the necessary diverse data types (e.g. data from lab tests, medical imaging, wearables, sensors, medical check-ups, mHealth devices, longitudinal health monitoring etc.) should be demonstrated and the sex/gender dimension should be investigated.
• Integrate standardised spatiotemporal multi-scale models as a basis for developing personalised ‘virtual twin’ models taking account of patient individual characteristics, medical and health status history for advancing personalised disease management. Proposals should ensure that the development of ‘virtual twin’ models is driven by the end-users/citizens/healthcare professionals needs and their active involvement throughout the development process. Furthermore, applicants should utilise appropriate IT solutions for model visualisation and demonstrate their accessibility and usability for clinical uptake.
• Validate multi-scale patient-specific models and generate evidence that results can deliver clinically meaningful, real-world observations for the human diseases under study. Applicants should implement proof-of-concept, feasibility studies in relevant end user environments and/or real-world settings, and collect evidence of utility vis-à-vis current clinical practice. Dynamic ‘virtual twin’ models and simulations as clinical decision support tools will need be shown to improve prognosis, medical diagnosis, treatments and health outcomes across the continuum of diseases evolution, including co-morbidities and long-term care as appropriate. An exploitation strategy and a business plan, including regulatory and industrial input, should be developed for accelerating clinical and/or market uptake.