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News

17 November 2024

QSPainRelief PhD students receive awards at SIF Congress

We proudly congratulate the consortium’s early career scientists (ECS), Elisabetta Cuna (PI: Andrea Bedini) and Chiara Cimetti (PI: Monica Baiula) from partner UNIBO, for being awarded one of approximately 15 «Best Oral Communication» and «Best Poster» awards, respectively, at the National Congress of Italian Society of Pharmacology (Società Italiana di Farmacologia – SIF) that took place in Sorrento, Italy, from 13-16 November 2024. Title of Elisabetta’s oral presentation: «Quantitative Systems Pharmacology platform to predict optimal drug combinations for chronic pain: Evaluation of morphine and pregabalin potential interaction in neuronal cell models«. Title of Chiara’s poster: «In-vitro investigation of Mu opioid receptor (MOR) interfacial residues computationally predicted to have a role in MOR/cannabinoid receptor 1 (CB1) heteromerization and crosstalk basally and in response to morphine treatment.»

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Events

25 March 2025

Solenn Gousset completes her PhD – congratulations!

We cordially congratulate Solenn Gousset from André Mouraux’s group at QSPainRelief partner Université catholique de Louvain (UCL) for successfully defending her PhD thesis on March 25th 2025 – what an accomplishment! Her thesis is entitled «Novel approaches to investigate central sensitization: From experimental models to clinical perspectives».

Solenn’s dedication and work remains an integral part of the QSPainRelief consortium and the project’s aims to better understand the neuroscientific mechanisms of pain, pain pathways, central sensitisation, and the development of chronic pain.

Jeroen Elassaiss-Schaap from QSPainRelief partner PD-value also served as part of the PhD jury / committee.

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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