CORDIS - Risultati della ricerca dell’UE
CORDIS

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

Descrizione del progetto

Un nuovo modo per combattere il dolore cronico

Per dolore cronico si intende un dolore che dura a lungo, anche dopo la guarigione di una lesione. Colpisce oltre il 20 % della popolazione causando problemi nella vita di tutti i giorni. Il dolore cronico viene trattato con una combinazione di diversi farmaci analgesici, somministrati secondo la decisione di ciascun medico in base alle proprie migliori esperienze. Questo spesso non risulta efficace e potrebbe persino avere effetti dannosi. Il progetto QSPainRelief, finanziato dall’UE, svilupperà una piattaforma per migliorare il trattamento e alleviare il dolore cronico con un’efficace combinazione di farmaci grazie a un meccanismo di farmacologia dei sistemi quantitativi basato sulla modellistica matematica (modellistica in silico). Ciò consentirà ai medici di identificare e testare una terapia efficace e mirata attraverso la combinazione intelligente di farmaci per ogni caso di paziente.

Obiettivo

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.

Invito a presentare proposte

H2020-SC1-BHC-2018-2020

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Bando secondario

H2020-SC1-2019-Two-Stage-RTD

Meccanismo di finanziamento

RIA - Research and Innovation action

Coordinatore

UNIVERSITEIT LEIDEN
Contribution nette de l'UE
€ 1 404 207,50
Indirizzo
RAPENBURG 70
2311 EZ Leiden
Paesi Bassi

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Regione
West-Nederland Zuid-Holland Agglomeratie Leiden en Bollenstreek
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
€ 1 404 208,00

Partecipanti (9)