The practice of medicine is based on predictions. As clinicians, we must predict if certain symptoms are representative of disease (diagnosis), the severity with which a disease will manifest (prognosis) or the effect of interventions in moderating or resolving such disease (treatment planning).

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Clinicians frequently make decisions based upon data pooled from randomised controlled trials, which can be problematic.

First, these population-level data are extrapolated and applied to individuals.

Second, randomised trials frequently recruit younger, otherwise well patients, and therefore under-represent the “average” patient who is typically older, with multiple comorbidities.

Medicine requires an approach more tailored to the individual patient, based upon patient-specific characteristics. This can be achieved with in silico medicine.

Patient specific predictive medicine technology

It is possible to generate computer models that transform patient-specific data from medical imaging, biomedical instrumentation, laboratory analyses, and clinical observation, into patient-specific predictions of clinically relevant quantities.

This opens a new scenario, where we can improve the quality and the quantity of healthcare through the development of technologies capable of predicting clinically relevant information about individual patients, hereinafter referred as Predictive Medicine technologies.

Insigneo is the largest research institute in Europe entirely dedicated to this topic, and it includes among its ranks some of the most respected specialists in the world. 

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