O-Health

The O-Health project aims to advance in the prevention of noncommunicable diseases that, due to the invisibility of their initial symptoms, are complex to diagnose. Such diseases include atherosclerosis, the degeneration of the intervertebral discs, knee osteoarthritis, and pulmonary emphysema.

Non-communicable diseases (NCD) that involve load-bearing organs emerge silently according to complex mechanisms that are likely to involve inter-disease systemic communications. Clinical explorations cannot apprehend such intricate emergence, but I postulate that multiscale in silico models can.

The digital twin for health has progressed a lot in the last decades, but multi-disease transversal modelling has not happened. It requires unique developments to couple small to large-scale model components with appropriate balance of phenomenological and mechanistic approaches, to cope with overwhelming biological complexity, preserve interpretability and incorporate real-world data. This is the niche of O-Health that proposes a scalable ecosystem of multiscale NCD models interrelated through a systemic model of low-grade inflammation.

The project tackles such vertical and transversal physiology-based computational modelling through four major NCD, lung emphysema, atherosclerosis, intervertebral disc degeneration and knee osteoarthritis that affect load-bearing organs at different anatomical locations. The cellular /molecular scale components of each NCD model will vertically share predicted variables with an interface model of endothelial cell dysfunction that communicates with a transversal model of body-wide systemic communications.

The O-health ecosystem will be modular and interoperable. Mechanistic modelling will be covered by finite element models at the organ /tissue scales and by agent-based (AB) models at the cell /molecular scales. AB models will incorporate highlevel interaction graphs for interpretable phenomenological modelling where necessary. Graphs will merge knowledge projection and correlation models extracted from longitudinal population cohort data, also used to evaluate O-Health. Interoperability will be ensured through standard languages such as Field and Systems Biology Mark-up Languages, enabling the scalability of the O-Health ecosystem.

This project has received funding from the European Research Council
ERC Consolidator Grant number: ERC-2021-COG-101044828
Dates: 01/11/2022 - 31/10/2027