DC-ren SIGNED
Drug combinations for rewriting trajectories of renal pathologies in type II diabetes (DC-ren)
Total Cost €
0EC-Contrib. €
0Partnership
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0DC-ren project word cloud
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Project "DC-ren" data sheet
The following table provides information about the project.
| Coordinator |
MEDIZINISCHE UNIVERSITAT INNSBRUCK
Organization address contact info |
| Coordinator Country | Austria [AT] |
| Total cost | 5˙968˙480 € |
| EC max contribution | 5˙968˙480 € (100%) |
| Programme |
1. H2020-EU.3.1.1. (Understanding health, wellbeing and disease) |
| Code Call | H2020-SC1-2019-Two-Stage-RTD |
| Funding Scheme | RIA |
| Starting year | 2020 |
| Duration (year-month-day) | from 2020-01-01 to 2024-12-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | MEDIZINISCHE UNIVERSITAT INNSBRUCK | AT (INNSBRUCK) | coordinator | 1˙045˙300.00 |
| 2 | MEDIZINISCHE UNIVERSITAET WIEN | AT (WIEN) | participant | 948˙800.00 |
| 3 | EMERGENTEC BIODEVELOPMENT GMBH | AT (VIENNA) | participant | 898˙775.00 |
| 4 | UNIVERSITA CA' FOSCARI VENEZIA | IT (VENEZIA) | participant | 781˙405.00 |
| 5 | MOSAIQUES DIAGNOSTICS GMBH | DE (HANNOVER) | participant | 701˙050.00 |
| 6 | ACADEMISCH ZIEKENHUIS GRONINGEN | NL (GRONINGEN) | participant | 554˙925.00 |
| 7 | REGION HOVEDSTADEN | DK (HILLEROD) | participant | 522˙987.00 |
| 8 | WEIZMANN INSTITUTE OF SCIENCE | IL (REHOVOT) | participant | 515˙237.00 |
Map
Project objective
Diabetic Kidney Disease (DKD) is highly prevalent in type 2 diabetes, with major impact on patients and healthcare systems. The complex disorder, further modulated by cardiovascular comorbidities, presents as an accumulation of risk factors, which we treat with drug combinations. While the overall benefit of this approach is evident on a cohort level, individual patients show remarkable heterogeneity in drug response, and lack of guidance on personalized medication results in suboptimal control of the disorder. For resolving variability, we propose a new concept for personalization of drug combinations beyond the cohort-centric perspective. We improve patient stratification based on equivalence relations of clinical presentation, disease pathophysiology and drug combinations. The approach is derived from dynamical systems theory, aimed at reducing probabilistic assignment of patient-specific disease evolution and matching drug combinations. The availability of a large European repository holding DKD patients in routine care with diverse drug combinations, complemented by high-throughput screening for improving patient phenotyping, and molecular network modelling of pathology, embedded risk factor combinations and consequence of drug effect allows a systems representation of patient groups. Integrating clinical presentation and molecular architecture in a novel computational framework will establish a decision support software prototype. We will validate this tool for predicting optimized personalized drug combinations in a study using given clinical trial repositories. Demonstration will expand to other available drugs, which in combination with approved drugs promise benefit for groups of DKD patients. With a clear route toward uptake in the clinical setting, and generalization capacity of our approach to other complex disorders we foster next steps in personalization, anticipate major patient benefit, and see novel translation and business opportunities.
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