BIGPICTURE - BIGPICTURE
Central Repository for Digital Pathology
BIGPICTURE, a pathology-led project, has the vision to become the catalyst in digital transformation in Pathology. Our mission is to create the first European GDPR compliant platform, in which both quality-controlled Whole Slide Imaging (WSI) data and advanced Artificial intelligence (AI) algorithms will exist.
The BIGPICTURE platform will be built on existing assets of ELIXIR EU data infrastructure, including the federated European Genome-phenome Archive (EGA) technology for managing the exchange of confidential information between contributors and users. The consortium will use Cytomine, an established open-source, cross-platform framework to develop unique tools for access to WSI, including annotations and visualisation of algorithm results, while we will develop new and generic models to facilitate AI development and mining of WSI data. By engaging and building consensus with all the relevant stakeholders, we will contribute to the development of a regulatory framework for digital slides and AI-based methods. Finally, BIGPICTURE envisions sustainability of its platform through a community- based model which relies on reciprocity, value creation and inclusiveness.
To achieve our vision, we have brought together Europe’s leaders in the field of computational pathology who have access to national and European high-performance computing infrastructures as well as Europe’s fully digitalised pathology departments. Additionally, the consortium has currently access to approximately 4.5 million clinical WSI covering a wider range of indications through 17 partners and 23 third parties from the largest European and international pathology and trial groups. Our consortium is further strengthened by the presence of the European Society of Pathology, Digital Pathology Association, FDA and 9 SMEs as partners, while we are further supported by professional societies, and patient advocates.
This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 945358. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA.