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News

17 November 2020

First publication of the project by Jesús Giraldo

The first QSPainRelief publication on the statistics of molecular dynamics simulations is out! Congrats to Prof. Jesús Giraldo and colleagues from Institut de Neurociències (INc) at the Universitat Autònoma de Barcelona (UAB) on this achievement!

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Events

09-10 December 2020

2nd GA Meeting in December 2020

Originally planned in Cologne, the 2nd QSPainRelief General Assembly (GA) Meeting meeting took place from 09-10 December 2020 via Zoom. Please refer to Twitter and LinkedIn for updates form the meeting itself. We were also excited to have the SEAB members present and to hear about the first research results of our early-career scientists (ECS)!

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Personalise and maximize pain relief for individuals suffering from chronic pain

Summary Statement

10 institutions in Europe and the USA collaborate for the next 5 years to help patients suffering from chronic pain. QSPainRelief aims to develop effective drug combination treatments for the improved relief of chronic pain. A quantitative systems pharmacology (QSP) mathematical modelling approach will be used to identify and validate more effective therapeutic interventions by smart combinations of existing drugs. The ultimate goal is to personalise and maximize pain relief for individuals suffering from chronic pain while diminishing side effects.

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Objectives

  • Consolidating cutting-edge treatment models for chronic pain
  • Summary Statement
  • Validating novel combinational therapies preclinically in vitro and in vivo
  • Conducting clinical studies to detect functional biomarkers
  • Improving the clinical guidelines for pain relief in stratified patient groups
  • Personalising pain relief treatment for each patient
  • Improving the scientific understanding of chronic pain regarding age, sex, disease and genetic factors

Impact

  • Novel concepts of combinational pain relief therapies
  • Improved efficacy and acceptability in the clinic
  • Effective stratification of patients with respect to age, sex, disease and genotype
  • Personalised treatment with unswerving benefits for patients
  • Unique knowledge gain and innovation opportunities