Descripción del proyecto
Una nueva forma de luchar contra el dolor crónico
El dolor crónico es aquel que se mantiene durante mucho tiempo, incluso después de que se cure la lesión. Afecta a más del 20 % de la población y causa problemas en la vida cotidiana. El dolor crónico se trata mediante una combinación de varios analgésicos que se administran según el criterio de cada médico a partir de su propia experiencia. A menudo, esto no resulta eficaz e incluso puede tener efectos nocivos. El proyecto financiado con fondos europeos QSPainRelief desarrollará una plataforma para mejorar el tratamiento y aliviar el dolor crónico mediante una combinación eficaz de fármacos gracias a un mecanismo de farmacología de sistemas cuantitativos basado en modelos matemáticos (modelado «in silico»). Permitirá a los médicos identificar y probar terapias eficaces y personalizadas a través de una combinación inteligente de fármacos específica para cada paciente.
Objetivo
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.
Ámbito científico
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SC1-2019-Two-Stage-RTD
Régimen de financiación
RIA - Research and Innovation actionCoordinador
2311 EZ Leiden
Países Bajos