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

Project description

DEENESFRITPL

New way to fight chronic pain

Chronic pain is pain that lasts a long time, even after an injury heals. It affects more than 20 % of the population causing problems in everyday life. Chronic pain is treated with a combination of several analgesic drugs administered according to each physician’s decision based on their own best experiences. This is often not effective and it could even cause harmful effects. The EU-funded QSPainRelief project will develop a platform to improve treatment and relieve chronic pain with an effective combination of drugs thanks to a mechanism of quantitative systems pharmacology based on mathematical modelling (in silico modelling). It will allow physicians to identify and test effective, personally targeted therapy through the smart combination of drugs for each patient case.

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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Call for proposal

H2020-SC1-BHC-2018-2020

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Sub call

H2020-SC1-2019-Two-Stage-RTD

Funding Scheme

RIA - Research and Innovation action

Coordinator

UNIVERSITEIT LEIDEN
Net EU contribution
€ 1 404 207,50
Address
Rapenburg 70
2311 EZ Leiden
Netherlands

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Region
West-Nederland Zuid-Holland Agglomeratie Leiden en Bollenstreek
Activity type
Higher or Secondary Education Establishments
Links
Other funding
€ 0,50

Participants (9)

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Last update: 24 November 2023

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Permalink: https://cordis.europa.eu/project/id/848068

European Union, 2023