Objective
Traditional preclinical discovery methods, particularly for target validation, poorly predict drug efficacy, causing a high attrition rate in costly late-stage clinical trials. The PREDECT consortium will focus on complex but transferable, next generation in vitro and in vivo models for breast, prostate and lung cancers. Models will be investigated for their improved potential to validate novel therapeutic targets. Known targets, in canonical pathways, will be interrogated for induction of phenotypic, proteomic and transcriptomic changes using inhibitors. A strategy of seeking a ‘dynamic reciprocity’ of concordance between the steady and perturbed states of in vitro complex cultures, tissue slices and in vivo tumour models will be pursued by systems biology analyses. Comparison with historic gene expression and genomic data from relevant clinical materials should permit the emergence of faithful models for target validation and beyond.
PREDECT is coordinated by Servier and AstraZeneca, and the managing entity of IMI JU funding is the University of Helsinki. The team assembles world-class biologists, clinicians and computational scientists from 8 prestigious EU institutes, 3 SMEs and 8 EFPIA members to develop and critically assess models for target validation. The interaction between pharmaceutical and academic participants will be proactive, through postdoc co-supervision and work package co-piloting.
We propose to develop and generate a repository of advanced complex models in 3 complementary areas: (i) in vitro 2D/3D organotypic (co-)cultures, stirred bioreactor aggregates and tissue slice systems; (ii) novel (orthotopic) grafts of human and mouse tumour samples; and (iii) genetically-engineered and mosaic mouse models. The deliverables of PREDECT are expected to shift paradigms in target validation, permitting greater predictivity of drug efficacy in patient cohorts.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyenvironmental biotechnologybioremediationbioreactors
- medical and health sciencesclinical medicineoncologylung cancer
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Call for proposal
IMI-JU-02-2009
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Coordinator
91190 GIF-SUR-YVETTE
France
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Participants (20)
00014 HELSINGIN YLIOPISTO
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Participation ended
02044 VTT ESPOO
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1015 Lausanne
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7610001 Rehovot
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2781-901 Oeiras
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6525 XZ Nijmegen
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3015 GD Rotterdam
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51005 Tartu
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79108 Freiburg
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00290 Helsinki
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151 85 Sodertaelje
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13353 Berlin
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02200 Espoo
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4070 Basel
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Participation ended
00144 Roma
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55218 Ingelheim
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70376 Stuttgart
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2340 Beerse
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CF24 0DE Cardiff
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60064 North Chicago Il
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