Opendata, web and dolomites

RESCUER SIGNED

RESISTANCE UNDER COMBINATORIAL TREATMENT IN ER+ AND ER- BREAST CANCER.

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 RESCUER project word cloud

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

women    approved    solid    sub    breast    first    drug    model    signatures    alternative    computer    biological    ex    ongoing    vs    few    silico    newly    cancer    integrate    arbitrary    tested    responders    death    framework    despite    samples    heterogeneity    molecular    treatment    effectiveness    therapy    actually    combinations    trials    combine    network    discover    ethics    overreaching    drugs    personalized    cellular    individual    vivo    animal    subtypes    patient    data    degree    worldwide    purpose    classified    everyone    algorithms    curative    thin    benefit    multidimensional    stratification    therapies    combinatorial    strata    predict    aspects    longitudinal    bc    mechanisms    combination    endowed    clinical    physiological    computational    organ    administering    exploring    probability    ethical    indication    patients    frameworks    models    omic    omics    resistance    optimization    tried    efficient    tumor    xenograft    gather   

Project "RESCUER" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITETET I OSLO 

Organization address
address: PROBLEMVEIEN 5-7
city: OSLO
postcode: 313
website: www.uio.no

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 Norway [NO]
 Total cost 6˙283˙250 €
 EC max contribution 6˙000˙000 € (95%)
 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    UNIVERSITETET I OSLO NO (OSLO) coordinator 933˙543.00
2    HELSINGIN YLIOPISTO FI (HELSINGIN YLIOPISTO) participant 946˙443.00
3    OSLO UNIVERSITETSSYKEHUS HF NO (OSLO) participant 935˙625.00
4    UNIVERSITAT DE BARCELONA ES (BARCELONA) participant 466˙337.00
5    VIB BE (ZWIJNAARDE - GENT) participant 464˙375.00
6    KAROLINSKA INSTITUTET SE (STOCKHOLM) participant 424˙781.00
7    CONSORCI INSTITUT D'INVESTIGACIONS BIOMEDIQUES AUGUST PI I SUNYER ES (BARCELONA) participant 400˙000.00
8    COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES FR (PARIS 15) participant 389˙012.00
9    INTERDISCIPLINARY CENTER (IDC) HERZLIYA IL (HERZLIYA) participant 371˙875.00
10    THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE UK (CAMBRIDGE) participant 273˙000.00
11    UNIVERSITATSKLINIKUM ERLANGEN DE (ERLANGEN) participant 245˙712.00
12    INSTITUT FUR FRAUENGESUNDHEIT GMBH DE (ERLANGEN) participant 141˙293.00
13    RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY US (NEW BRUNSWICK) participant 8˙000.00
14    NANTOMICS LLC US (DOVER) participant 0.00
15    NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU NO (TRONDHEIM) participant 0.00

Map

 Project objective

Breast Cancer (BC) is the first cause of cancer-related death in women worldwide. Breast cancer is classified into well-recognized molecular subtypes. Despite solid pre-clinical evidence, only some patients benefit from administering drug combinations, an indication that patient and tumor heterogeneity is still present in the current stratification. Out of the numerous possible combinations of approved drugs, only a few have been actually tried, and the choice of tested combinations has been to some degree arbitrary. This proposal seeks to develop new approaches and identify mechanisms of treatment resistance at systems level, exploring how the effectiveness of specific targeted therapies applied in different clinical trials is affected by patient- and tumor-specific conditions. For this purpose, the project will gather and integrate longitudinal multidimensional data from ongoing clinical trials and newly generated --omics using systems approaches, which combine sub-cellular/cellular and/or organ level in-silico models and network analysis to build computational frameworks able to discover molecular signatures of resistance and predict patient response to combinatorial therapies. We aim to identify the physiological characteristics of non-responders vs. responders from existing and newly generated multi-omic data and biological samples from in-vivo and ex-vivo clinical studies of specific subtypes of BC patients treated with combination therapy. This new knowledge will be used to investigate the curative potential of new personalized drugs combinations. The overreaching goal is to develop computer “xenograft model” as a cost-efficient and better alternative in terms of ethics, availability to everyone, and animal use. The framework will include optimization algorithms to identify combinations of approved drugs with a high probability to work on individual or thin strata of patients. The project is endowed with a “legal” framework addressing ethical aspects

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "RESCUER" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "RESCUER" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.3.1.1.)

DECISION (2020)

DECOMPENSATED CIRRHOSIS: IDENTIFICATION OF NEW COMBINATORIAL THERAPIES BASED ON SYSTEMS APPROACHES

Read More  

CoMorMent (2020)

Predicting comorbid cardiovascular disease in individuals with mental disorder by decoding disease mechanisms

Read More  

SoNAR-Global (2019)

A Global Social Sciences Network for Infectious Threats and Antimicrobial Resistance

Read More