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DC-ren SIGNED

Drug combinations for rewriting trajectories of renal pathologies in type II diabetes (DC-ren)

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 DC-ren project word cloud

Explore the words cloud of the DC-ren project. It provides you a very rough idea of what is the project "DC-ren" about.

risk    disease    generalization    validate    pathophysiology    resolving    guidance    personalized    predicting    demonstration    individual    relations    dynamical    prevalent    representation    translation    route    matching    prototype    drug    trial    repository    reducing    medication    cohort    phenotyping    perspective    diabetes    equivalence    toward    centric    disorder    molecular    setting    see    architecture    probabilistic    approved    lack    business    healthcare    expand    routine    optimized    modulated    personalization    combination    evolution    network    treat    benefit    promise    cardiovascular    patients    disorders    tool    diverse    complemented    diabetic    drugs    clinical    framework    presentation    suboptimal    assignment    evident    care    clear    dkd    groups    pathology    anticipate    stratification    accumulation    consequence    heterogeneity    kidney    variability    combinations    screening    effect    repositories    holding    throughput    comorbidities    theory    integrating    software    remarkable    patient    decision    capacity    computational   

Project "DC-ren" data sheet

The following table provides information about the project.

Coordinator
MEDIZINISCHE UNIVERSITAT INNSBRUCK 

Organization address
address: CHRISTOPH PROBST PLATZ 1
city: INNSBRUCK
postcode: 6020
website: www.i-med.ac.at

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 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.

# participants  country  role  EC contrib. [€] 
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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The information about "DC-REN" are provided by the European Opendata Portal: CORDIS opendata.

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