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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.

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

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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