Collaborations between academic institutions and the diagnostics/pharmaceutical industry are increasingly being initiated and executed. It's assumed that these relationships could help to improve research and development productivity in industry, as well as enable academic institutions to better exploit the translational potential of their research. Identification and validation of targets and biomarkers, key elements of successful drug discovery, are challenging. Unfortunately according published data are frequently irreproducible. Thus we must not rely on published data only. Extensive joined efforts of multiple partners seem crucial to foster progress. Different models are used and required for different stages of the drug discovery and development process as well as for different kinds of targets and biomarkers. There isn't a ?one size fits all? solution. For the initial exploration of a new biomarker candidate, a novel technology, or a new target a project within a strategic partnership or an open innovation approach may be most suitable. For the comprehensive clinical validation, however, larger consortia may be more appropriate, as this requires high resources and complementary skills. We expect the high number of academic-industrial collaborations will further increase, in part (but not only) due to the increasingly availability of public funding. Each category of collaboration has its own needs to be successful. However, there are some general elements too
