Project streams

Problem statement

Aimed to improve understanding and diagnosis of medical conditions by advancing the use of physiological models and their predictions in clinical practice.

Framework for personalised physiome modelling

We developed and tested approaches toward an energy-based multiscale framework for modelling person-specific human physiology and pathology.

Enabling development and clinical translation of virtual human twins

We developed the open-source 12 Labours Digital Translational Workflows for Integrating Systems (DigitalTWINS) AI platform infrastructure to support collaborative workflows for creating and testing personalised digital twins.

Imaging the human body

We developed an imaging platform that captures body surface geometry coupled with data from medical and wearable devices.

Wearable and implantable devices

We developed data transfer systems for wearable and implantable devices to support continuous calibration of Physiome models.

Predict response to treatment for pulmonary hypertension

We used patient data to create personalised pulmonary circulation models and explore virtual surgery approaches for predicting treatment response.

Personalised rehabilitation of upper limb disorders

We developed and validated pre-operative planning and post-operative monitoring technology for shoulder arthroplasty.

Expanding knowledge of uterine electrophysiology

We advanced understanding of electro-mechanical activity of smooth muscle organs to elucidate the essential drivers of uterine contraction and aid in diagnosis and monitoring of endometriosis and pregnancy.

Automated clinical workflows for breast cancer diagnosis and treatment

We created personalised models of the breast from dynamic contrast-enhanced MRI and apply them in clinical workflows for supporting breast cancer diagnosis.

Improve understanding of gut-brain interaction

We modelled the fluid transit behaviour of the colon, integrated with existing models of the microbiome, to gain a deeper understanding of the role of microbiome-host interaction in disorders of gut-brain interaction.

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