Explore the words cloud of the QSPainRelief project. It provides you a very rough idea of what is the project "QSPainRelief" about.
The following table provides information about the project.
Coordinator |
UNIVERSITEIT LEIDEN
Organization address contact info |
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 |
Take a look of project's partnership.
# | ||||
---|---|---|---|---|
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 |
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.