NOCI call for projects at EGAM 2009

Translational research is an essential component of the EORTC Scientific Strategy and contributes to the distinction between studies comparing treatment regimes and academically driven studies asking biologically relevant questions. The EORTC scientific strategy places a high priority on the latter, trials with a strong translational research component, and NOCI, a Network of Core Institutions within the EORTC, can facilitate implementation of this scientific strategy. NOCI provides a pan-European network upon which innovative trials with complex designs and translational research requiring specific expertise can be organized. It allows systematic, comprehensive and centralized collection of bio-samples from selected EORTC trials and makes high quality bio-sample collections and associated clinical data sets available to the EORTC network. The NOCI consortium agreement provides a set of general rules for performing NOCI projects including intellectual property, publication, and access rights with the aim of promoting and facilitating research projects and collaborations on translational research.

The NOCI call at EGAM 2009 was conceived to advance EORTC scientific strategy and NOCI projects, in particular, and to foster interaction between the EORTC divisions and the EORTC groups. A session dedicated to this call for NOCI projects will be held on 19 March 2009 from 14.00–19.30 at the EGAM 2009 meeting. The EORTC Board has agreed to allocate up to 1 000 000 euros for this initiative to help launch clinico-genomic trials which cannot be adequately supported by the pharmaceutical industry. Four to five grants are available and will be allocated after final evaluation by EORTC Board. The evaluation criteria include the originality, innovation, and adherence to EORTC scientific strategy, the likely impact of the study on clinical practice, the strength of the translational research component, the appropriateness of the methodology with respect to achieving the study objective, feasibility, and statistical robustness.