Coordinated by:Prof. Tim Hucho, Cologne
Funding period:Start  2012/2013


Current pain therapies leave hundreds of millions of patients in Western countries without adequate pain relief. Beyond its socio-economical costs, this reveals a striking lack of efficient drugs. In addition, deleterious therapeutical side effects are increasingly recognized reducing the usability of current pharmaceuticals.
Medical research recently started to aim for “mechanism-based pain therapy” in contrast to the current empirical treatment of symptoms (Rolke et al., 2006; Baron et al., 2010). But mechanisms-differentiating therapy approaches have to take into account an ever-increasing number of interconnected pain-components. In addition, it becomes increasingly obvious, that pain sensitization is the result of a multi-facetted/multi-parametric and most of all dynamic (!) transition between various pain-states.
Accordingly, current/classical research efforts focusing on one/few molecules at a time are granted limited success. Many if not most fail when tested in the complex and dynamic reality of an organism struggling after intense painful insults with tissue destruction and regeneration. Immense complexity, dynamic processes, and failure of current approaches are hallmarks for a switch to a systems biological approach aiming at novel mechanism-based and integrative therapeutic strategies. Two years ago, we started to establish an in silico model of components mediating pain sensitization in the world-wide first systems biology consortium working on pain, the BMBF funded consortium “Modeling of peripheral Pain Switches (MopS)”. Building upon this model, upon large numbers of data (high throughput as well as classical), and upon the established collaborative network, we now propose an ambitioned aim:
The “NoPain” consortium aims at the identification of pain-inhibiting mechanisms by detailed structural and dynamic (!) analysis of our existing in silico model of pain signaling. We further aim at translating novel inhibitory mechanisms from in silico via molecular, cellular, and behavioral model systems to first patient experiments.
Pursuing this goal we will broaden the existing model with further components by application of among others “Omics” approaches. And last but not least, we will actively attempt to anchor the systems biology approach within pain research, a scientific community so far mostly unfamiliar with this novel methodology.