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QSPainRelief SIGNED

Effective combinational treatment of chronic pain in individual patients, by an innovative quantitative systems pharmacology pain relief approach.

Total Cost €

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EC-Contrib. €

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Partnership

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 QSPainRelief project word cloud

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

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Project "QSPainRelief" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITEIT LEIDEN 

Organization address
address: RAPENBURG 70
city: LEIDEN
postcode: 2311 EZ
website: www.universiteitleiden.nl

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
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 Coordinator Country Netherlands [NL]
 Project website https://www.qspainrelief.eu/
 Total cost 6˙239˙539 €
 EC max contribution 6˙239˙538 € (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    UNIVERSITEIT LEIDEN NL (LEIDEN) coordinator 1˙404˙207.00
2    IN SILICO BIOSCIENCES, INC US (LEXINGTON MA) participant 1˙095˙875.00
3    UNIVERSITE CATHOLIQUE DE LOUVAIN BE (LOUVAIN LA NEUVE) participant 848˙320.00
4    STICHTING CENTRE FOR HUMAN DRUG RESEARCH NL (LEIDEN) participant 677˙636.00
5    UNIVERSIDAD POMPEU FABRA ES (BARCELONA) participant 585˙875.00
6    Concentris Research Management GmbH DE (Fürstenfeldbruck) participant 530˙000.00
7    ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA IT (BOLOGNA) participant 390˙875.00
8    UNIVERSIDAD AUTONOMA DE BARCELONA ES (CERDANYOLA DEL VALLES) participant 340˙875.00
9    PD-VALUE BV NL (HOUTEN) participant 298˙375.00
10    CLINIQUES UNIVERSITAIRES SAINT-LUC BE (BRUXELLES) participant 67˙500.00

Map

 Project objective

Chronic pain is a complex disease suffered by about 20% of Europeans. Up to 60% of these patients do not experience adequate pain relief from currently available analgesic combinational therapies and/or suffer confounding adverse effects. Of the many conceivable combinations only a few have been studied in formal clinical trials. Thus, physicians have to rely on clinical experience when treating chronic pain patients. The vision of the QSPainRelief consortium is that alternative novel drug combinations with improved analgesic and reduced adverse effects can be identified and assessed by mechanism-based Quantitative Systems Pharmacology in silico modelling. This is far cheaper and less time-consuming than clinical trials. We will develop an in silico QSPainRelief platform which integrates recently developed 1) physiologically based pharmacokinetic model to quantitate and adequately predict drug pharmacokinetics in human CNS, 2) target-binding kinetic models; 3) cellular signalling models and 4) a proprietary neural circuit model to quantitate the drug effects on the activity of relevant brain neuronal networks, that also adequately predicts clinical outcome. This platform will include patient characteristics such as age, sex, disease status and genotypes, and will predict efficacy and tolerability of a wide range of analgesic and other centrally active drug combinations, and rank these. The best combinations will then be validated in a suitable animal model, in two clinical studies in healthy volunteers, as well as in real world clinical practice. Quantitative insights and confirmed effective combinational treatments will result in a game-changer by improving the management of pain in individuals and stratified sub-populations of chronic pain patients, and reduce the large burden on health-care providers greatly. It would also increase the understanding of chronic pain in general, and trigger the development of even better combination therapies in the future.

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

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