Sepsis is a serious condition of infection and inflammation that can rapidly lead to tissue damage and organ failure. Detection and treatment are difficult, causing the condition to be fatal in many cases.

Digital Twin

A Digital Twin is a digital replica of a physical object. In this case we are developing a Digital Twin of a patient. This digital replica allows researchers to observe the patient in real time while simulating and predicting a the clinical outcome given different scenarios.

Overview of the sepsis detection and treatment workflow (black) and the Patient Digital Twin (blue).

The patient Digital Twin will combine continuous vital sign data, biochemical data and model predictions to create a digital replica of the patient. This Digital Twin is a tool that provides the clinical team decision support.



Optimize and personalize drug therapy in patients on the ICU.


Detect unusual patient progression and provide clinical decision support.


Develope and use disease and patient models to simulate clinical outcomes.

About us

We are a collaboration between Eindhoven University of Technology, Erasmus Medical Center and Radboud University Medical Center. Our goal is to develop a patient Digital Twin that can be used to improve sepsis detection and management.


Matthijs Kox

Assistant Professor of Intensive Care Medicine

Natal van Riel

Professor of Biomedical Systems Biology

Menno Prins

Professor of Molecular Biosensing

Freek Relouw

PhD candidate


Birgit Koch

Professor of Clinical Pharmacometrics

Rob Taal

Pediatrician and Neonatologist

Radboud UMC

TU Eindhoven

TU Eindhoven

TU Eindhoven

Erasums MC

Radboud UMC

Erasmus MC

Erasmus MC

Talk to us

Have any questions? We are always open to talk about collaborations, new projects and other opportunities.