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Building digital twins for effective & personalized medicine

Computer models to predict disease prognosis, health care needs, and fight future pandemics


Key points from article :

Digital twins are software replicas of the dynamic function and failure of engineered products and processes.

The medical analog could integrate human physiology and immunology with patient-specific clinical data to produce predictive computer simulations.

Combining mechanistic knowledge, observational data, medical histories, and the power of AI.

Could greatly reduce the cost and complexity of combinatorial clinical applications.

Used to derive predictions about diagnosis, prognosis, and efficacy and optimization of therapeutic interventions.

A digital twin to guide individual treatment is currently out of reach.

Laboratories and research groups around the world to integrate and validate submodels independently.

Require collection of synchronous measurements at different physiological scales.

Initially, repurposing to other diseases where the immune system is key, such as cancer.

Digital twins could be coupled to other disease-specific twins.

Study published in the Journal Science.

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Peer-reviewed academic online journal of the American Association for the Advancement of Science (AAAS)

Topics mentioned on this page:
Digital Modeling