Project Objectives

There is a strong need in biomedical research, especially in the case of complex heterogeneous diseases such as cancer, to achieve an all-comprising harmonization of efforts: To integrate the available data and knowledge in comprehensive models supported by interoperable infrastructures and tools, to standardize methodologies, and to achieve wide-scale data sharing and reuse, and multidisciplinary collaboration.

INTEGRATE aims to build solutions that support a large and multidisciplinary biomedical community ranging from basic, translational and clinical researchers to the pharmaceutical industry to collaborate, share data and knowledge, and build and share predictive models for response to therapies, with the end goal of improving patient outcome. Moving away from empirical medicine, towards evidence-based personalized care has the potential to both dramatically improve patient outcome and to reduce costs. INTEGRATE will deliver reconfigurable infrastructure components; tools for sharing and collaboration; standards-based data models; and repositories of data, models and knowledge.

The INTEGRATE environment will enable: Collection, preservation, management and reuse of data collected within multi-centric clinical trials. These unique comprehensive datasets will be made available through uniform interfaces to support information sharing and collaborative knowledge generation. Multi-disciplinary collaboration, providing an environment and tools that support researchers across domains, institutions and industries to jointly contribute to research objectives, develop common methodologies and complex analyses, and efficiently make use of each other's expertise and results. Collaborative definition and development of relevant clinical questions and more efficient validation of potential biomarker results and predictive models in clinical trials.

Collaborative development, preservation and sharing of multi-scale realistic and validated predictive models of response to novel therapies and anti-cancer drugs. We will propose methodologies for model development, a modelling framework, and predictive multi-scale models in the context of breast cancer. INTEGRATE will also provide standards-based interoperability to existing research and clinical infrastructures to support efficient information reuse and integration.