Under the leadership of prof. dr. Liesbet Geris and in the context of the EC funded EDITH project, a pan-European vision for the Virtual Human Twin is developed, as well as a roadmap for its realisation. The Virtual Human Twin is an integrated multi-level, -time and -discipline digital representation of the whole body enabling the comprehensive characterisation of the physiological and the pathological state in its heterogeneity, allowing patient-specific predictions for the prevention, prediction, screening, diagnosis and treatment of a disease, as well as the evaluation, optimisation, selection and personalisation of intervention options.

More practically, the Virtual Human Twin is an ever-growing accumulation of all quantitative knowledge on how individual subjects' health status changes over time. All knowledge is digitally stored in the form of adequately annotated data and predictive models. Observational data capture empirical knowledge, whereas predictive models capture causal knowledge. Data and models must be annotated with enough information to assess their credibility.

The outcome is anticated to be an agenda to produce a position paper in a high impact journal. It should also lead to an ELSI manifesto for the Virtual Human Twin community in Europe and beyond and could contribute to policy recommendations.

This in an invitation-only event.