ERC Grant MODEST
|Research in the fields of Mathematics and Health
|European collaborative research funded by HORIZON 2020, Excellent Science, ERC Consolidator Grant
|Term: 01.07.2015 to 30.06.2020|
|Project costs: 1,998,500 €, of which OVGU 1,998,500 €|
|Coordinator: Otto von Guericke University Magdeburg, Germany|
Development of mathematical models for the personalised medicine of the future
As part of the “Mathematical Optimisation for Clinical Decision Support and Training” (MODEST) project funded by the European Research Council (ERC), Professor Dr. Sebastian Sager and his team of mathematicians and clinicians from the University of Magdeburg are pursuing mathematical solutions that will support medical doctors in diagnostic and therapeutic decision-making and facilitate the development of personalised medicine. The aim of the project is to develop prototype mathematical models and algorithms that are able to integrate the many individual pieces of medical data that are collected and available. It should thus be possible to translate the mass of existing patient data into suggested diagnoses and therapies.
“Every day medical doctors have to make important decisions under time pressure. Cardiologists must find the possible causes of discrepancies using an ECG in just minutes, whilst oncologists must determine the dose and treatment duration of chemotherapy using laboratory markers,” says Professor Sebastian Sager. “These complex decisions are usually based on the expert knowledge they have acquired over the course of many years, but is not available to all patients and also cannot be easily transferred. There again, huge quantities of data are collected in clinics and medical practices, and in our view these are not adequately utilised for medical decision-making. Our mathematical models aim to make use of them in all their complexity whilst simultaneously extracting the essential information. We hope to develop software that is able to handle the abundance of data and support the decision-making of clinicians transparently and on the basis of facts.
In the same way that a flight simulator is able to train pilots to deal with different scenarios, disease simulators based on individual patient data could be used both in training and in everyday clinical practice to verify medical diagnoses and optimise therapeutic approaches. It would be possible to “project” the course of a disease and make it visible.
The project is funded by the European Research Council (ERC) as part of Horizon 2020, the EU Framework Programme for Research and Innovation (Grant Agreement No. 647573).