Project description
Dynamical systems theory could support physicians to select optimal therapies
Diseases, co-morbidities, and patients responses to certain therapies are the result of a complicated interplay of numerous factors. The relationships defining how this intricate network of inputs leads to various outputs is extremely difficult to derive using conventional means. Thanks to Big Data, high-level applied mathematics and computers, the EU-funded DC-ren project is developing a tool that will take all this and more into account, and enable optimised personalised drug therapies for significantly enhanced outcomes. The team is focusing on diabetic kidney disease, a common co-morbidity of type 2 diabetes often accompanied by cardiovascular disease. Currently, the drug cocktails targeting it produce highly varied responses. Thanks to its vast patient database, advanced experimental techniques and dynamical systems theory, DC-ren is developing a completely new and widely applicable computational framework for decision support.
Field of science
- /medical and health sciences/basic medicine/pathology
- /medical and health sciences/clinical medicine/endocrinology/diabetes/diabetic nephropathy
- /medical and health sciences/clinical medicine/nephrology/kidney diseases
- /natural sciences/mathematics/applied mathematics/dynamical systems
Call for proposal
H2020-SC1-2019-Two-Stage-RTD
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Funding Scheme
RIA - Research and Innovation actionCoordinator
6020 Innsbruck
Austria
Participants (7)
1180 Vienna
1090 Wien
30659 Hannover
9713 GZ Groningen
30123 Venezia
7610001 Rehovot
3400 Hillerod