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  Members Area

IMI | The Innovative Medicines Initiative
EFPIA | European Federation of Pharmaceutical Industries and Associations

Workpackage 10

Workpackage Objectives

  • Identify the optimal duration which reduces patient exposure and maximises efficacy information in schizophrenia.
  • Identify measures most sensitive to distinguishing active treatment vs. placebo-response in schizophrenia and depression.
  • Develop designs for more efficient trials by combining statistical tests of outcomes and optimizing symptom scales.
  • Use trajectories of treatment response (rather than simple responder/non-responder status) to identify and link to emerging biomarkers in schizophrenia.
  • Use the experience gained and the new techniques developed for Schizophrenia to apply them to studies and trials of depression as well as link with WP07-09.

Workpackage Leads

Academic Lead: Prof. Jonathan Rabinowitz, Bar Ilan University, Israel 
EFPIA Lead: Dr. Ivo Caers, Janssen Pharmaceutica NV, Belgium

Workpackage Partners

  • H. Lundbeck A/S
  • King’s College London
  • AstraZeneca AB
  • Eli Lilly and Company Ltd
  • GlaxoSmithKline Research and Development Ltd.
  • Pfizer Limited

Synergy between academia and industry

The project would not be possible without the contribution and pooling of data. Academics traditionally do not have access to these datasets. And individual companies themselves have access only to their data, thus limiting the generalizability of the results. In terms of expertise we draw upon the joint expertise on the acaedemic end (Kapur, Rabinowitz, Muthen, Tarpey, Uher) and EFPIA (Steckler, Gomeni, O’Gorman, Stauffer, Kinon, Zukin) and the evolving analytic approaches will be driven by a joint steering committee. Finally, the real test of the ideas will be the application in real prospective trials and the commitment on the part of EFPIA to implement these approaches in future trials.


WP10 - Advanced data analysis techniques for more efficient trials, biomarker identification and placebo-response differentiation