Description du projet
Un nouveau moyen de lutter contre la douleur chronique
La douleur chronique est une douleur qui dure longtemps, même après la guérison de la blessure. Elle affecte plus de 20 % de la population, entrainant ainsi des problèmes dans la vie quotidienne. La douleur chronique est traitée par une combinaison de plusieurs médicaments analgésiques administrés selon la décision de chaque médecin, basée sur leurs propres expériences. Ce traitement est souvent inefficace, et il pourrait même avoir des effets nuisibles. Le projet QSPainRelief, financé par l’UE, élaborera une plateforme pour améliorer ce traitement et soulager la douleur chronique avec une combinaison efficace de médicaments grâce à un mécanisme de pharmacologie des systèmes quantitatifs basé sur la modélisation mathématique (modélisation in silico). Il permettra aux médecins d’identifier et de tester une thérapie personnellement ciblée et efficace grâce à la combinaison intelligente de médicaments pour chaque patient.
Objectif
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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RIA - Research and Innovation actionCoordinateur
2311 EZ Leiden
Pays-Bas