Problem statement

The 12 Labours project aimed to improve understanding and diagnosis of medical conditions by bringing physiological models and their predictions into standard clinical practice.

A deeper understanding of the human body and physiology has continued to improve medical treatment and health outcomes. The project sought to advance understanding, treatment, and prediction of medical conditions through the development of computational physiological models—driving efforts to create accurate models that capture all scales of physiology, from the cell to the organ and the body as a whole system.

These models were driven by data. The project worked to expand both the sources and frequency of data available by utilising existing medical data, incorporating information from wearables, implantables, and home-based monitoring equipment, and developing new instruments and devices to capture new forms of physiological data.

The complexity of linking models across multiple scales and organs required a focus on standardisation and interoperability. The same applied to the data used to build these models, which needed to be stored in a standardised and secure way. This approach allowed data and models to be combined and run together within a unified framework.

1. A framework for personalised Physiome modelling. This allows users to combine models, link models across spatial and temporal scales, and to personalise the models.
2. A Physiome modelling platform for precision medicine. This allows medical professionals to implement personalised Physiome models in a clinical setting.
3. Continuous monitoring using workflows that will allow personalised Physiome models that can connect to wearable, implanted and home-based devices. This allows a continuous flow of data to update an individual’s personalised model for diagnostic monitoring and predicting therapeutic outcomes.