DeciPain

An integrated approach to anti-pain, drug discovery and validation of targets

Description

The goal of the present project is to overcome the current limitations of pain research by implementing a predictive in vivo pain model, to decipher spontaneous pain pathways, and to thoroughly evaluate drug effects on pain signaling.

Chronic and neuropathic pain, usually diagnosed as spontaneous pain, pain hypersensitivity, or both, is a maladaptive response of the body to injury and inflammation.


The search for new effective drugs to treat these debilitating conditions has proven particularly difficult, as agents with good efficacy in preclinical models often fail to meet clinical trial endpoints. A commonly accepted explanation for this discrepancy is that virtually all preclinical analgesic trials have limited predictability because they are based on models of evoked pain, whereas patients primarily seek relief of spontaneous pain.


To fill the gap in our knowledge of the mechanism of spontaneous pain and accelerate the discovery process towards better analgesics, we propose to implement a new in vivo platform to decipher pain pathways in animal models of spontaneous pain. A new electrophysiological approach, high-throughput microneurography (HT-MNG), will be implemented by using in-house nanotechnology and microelectronics. This approach will be combined and validated with in vivo RNA interference and optogenetics by specifically addressing targets known to be involved in chronic and neuropathic pain conditions.


The proposed in vivo preclinical platform has great translational potential as HT-MNG recordings from animal models provide data that are directly comparable to those from human patients. Therefore, we expect that our project will significantly help to avoid costly failures in Phase II and Phase III pain studies due to lack of drug efficacy. In addition, by being able to measure and recognize specific excitation patterns in peripheral neuropathies, the project may help to identify patients who are more likely to respond to a particular drug, dose or regimen, opening up new opportunities for personalized medicine.

Period:
01.09.2012 - 31.08.2016
FKZ:
322298
Funding:
EU MC Career Integration Grant
Management:
EU MC Career Integration Grant

Projectlead

Dr. Paolo Cesare

Organ-on-Chip