SciTransfer
POINT · Project

Predictive Risk Modeling and Biomarkers for Long-Term Post-COVID Organ Damage

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Imagine your body is like a house where a fire happened months ago; the fire is out, but some pipes are leaking and the wiring is frayed. This work identifies the specific 'leaks' in the heart, lungs, and kidneys using blood tests and digital clones of organs. It helps doctors spot who is at risk of permanent damage long after the initial sickness is gone.

By the numbers
183 million
reported COVID-19 cases in the EU
70%
patients suffering reduced organ function in the post-acute phase
5%
estimated people who suffered COVID-19 at risk of developing NCDs
6 million
Europeans in the analyzed cohorts
6000
Europeans in cross-sectional biobanks
The business problem

What needed solving

Healthcare systems lack tools to identify and treat patients who develop heart, lung, and kidney diseases months after COVID-19. This leads to high socioeconomic costs and missed opportunities for early prevention.

The solution

What was built

The project is building knowledge-based biomarkers, a virtual twin model for clinical decision support, and standardized clinical guidelines for post-acute COVID care.

Audience

Who needs this

Diagnostic kit manufacturersHealth insurance providersDigital health software companiesPublic health administration bodiesSpecialized cardiology and pulmonology clinics
Business applications

Who can put this to work

Diagnostics
mid-size
Target: Medical Laboratory Provider

If you are a lab provider dealing with a lack of specific tests for long-term recovery — this project developed knowledge-based biomarkers that allow for better targeted monitoring panels for heart, lung, and kidney health.

Digital Health
SME
Target: Health-Tech Software Developer

If you are a software developer dealing with the need for precise patient forecasting — this project developed a virtual twin model that simulates disease mechanisms to forecast individual risk for clinicians.

Healthcare Services
enterprise
Target: Private Clinic Network

If you are a clinic manager dealing with inconsistent patient follow-up protocols — this project developed clinical guidelines and decision support tools to help doctors act on risk in a consistent way across Europe.

Frequently asked

Quick answers

What is the cost or pricing for the virtual twin model?

Based on available project data, no specific pricing or cost structure for the model has been disclosed.

Can this be scaled to a global industrial level?

The project uses data from cohorts of more than 6 million Europeans and biobanks from over 6,000 people, suggesting a strong foundation for large-scale application.

How is the intellectual property or licensing handled?

Based on available project data, specific licensing terms are not mentioned, though the project works with standards bodies to ensure interoperability.

What regulations govern the clinical guidelines?

The project liaises with standards bodies to ensure that the emerging tools are usable, explainable, and interoperable in everyday care.

When will the tools be ready for clinical integration?

The project period runs from 2024-01-01 to 2027-12-31, indicating a timeline for development and validation through 2027.

Consortium

Who built it

The consortium is heavily weighted toward research and academia, with 3 universities and 2 research institutes. However, it includes a strategic mix of 10 partners across 8 countries, including 2 SMEs and 1 industrial partner. The inclusion of an end-user organization representing over 120,000 physicians provides a direct bridge to market adoption and clinical validation.

How to reach the team

Contact KOBENHAVNS UNIVERSITET regarding the POINT project coordination.

Next steps

Talk to the team behind this work.

Contact us to track the development of the virtual twin risk models for your diagnostic pipeline.

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