The central PANCAIM concept is to successfully exploit available genomic and clinical data to improve personalized medicine of pancreatic cancer. PANCAIM’s concept is unique as it integrates the whole spectrum of genomics with radiomics and pathomics, the three future pillars of personalized medicine. The integration of these three modalities is very challenging in the clinic, but also with AI. PANCAIM uses an explainable, data-efficient, two-staged AI approach. AI biomarkers transform the unimodal data domains into interpretable likelihoods of intermediate disease features. A second AI layer merges the biomarkers and responds with an integrated assessment of prognosis, prediction and monitoring of therapy response, to assist in clinical decision making. PANCAIM builds on four key concepts of AI in Healthcare: data providers, clinical expertise, AI developers, and MedTech companies to connect to data and bring AI to healthcare. Data quantity and quality is the main factor for successful AI. Partners provide eleven Pan European repositories of almost 6000 patients that are open to ongoing accrual. SME Collective Minds builds the GDPR data platform that hosts the data and provides a trustable connection to healthcare for even more and sustainable data. SME TheHyve builds tooling to connect to more genomic repositories (EOSC Health). Six Pan European academic centers provide clinical expertise across all modalities and help realize a curated, high quality annotated data set. Partners also include expert AI healthcare researchers across all clinical modalities with a proven track record. Finally, Siemens Healthineers provides their AI expertise and tooling to bring AI into healthcare for clinical validation and swift clinical integration in 3000 health care institutes.

Wide sharing of knowledge and data drives the progression of science. Shared data allows other researchers to reproduce findings and benchmark quality of experiments. Sharing data so that other researchers can Find, Access and Interoperate – i.e. integrate the data with the outcomes of their own experiments - allows Reuse and an opportunity to build the large aggregated cohorts we need to detect rare signals and manage the many confounding factors in translational research. This project will develop the guidelines and tools needed to make data FAIR. Through worked examples using IMI and EFPIA data and application and extension of existing methods we will improve the level of discovery, accessibility, interoperability and reusability of selected IMI and EFPIA data. In addition, through disseminated guidelines and tailored training for data handlers in academia, SMEs and pharmaceuticals, data management culture will change and be sustained and datasets will be reused by pharmaceutical companies, academia and SMEs. Our FAIR SME & Innovation programme will enable wide data reuse and foster an innovation ecosystem around these data that power future re-use, knowledge generation, and societal benefit. We call this approach ‘FAIRplus’.

FNS-Cloud will overcome fragmentation problems by integrating existing FNS data, which is essential for high-end, pan-European FNS research, addressing FNS, diet, health, and consumer behaviours as well as on sustainable agriculture and the bio-economy. Current fragmented FNS resources not only result in knowledge gaps that inhibit public health and agricultural policy, and the food industry from developing effective solutions, making production sustainable and consumption healthier, but also do not enable exploitation of FNS knowledge for the benefit of European citizens. FNS-Cloud will, through three Demonstrators; Agri-Food, Nutrition & Lifestyle and NCDs & the Microbiome to facilitate: (1) Analyses of regional and country-specific differences in diet including nutrition, (epi)genetics, microbiota, consumer behaviours, culture and lifestyle and their effects on health (obesity, NCDs, ethnic and traditional foods), which are essential for public health and agri-food and health policies; (2) Improved understanding agricultural differences within Europe and what these means in terms of creating a sustainable, resilient food systems for healthy diets; and (3) Clear definitions of boundaries and how these affect the compositions of foods and consumer choices and, ultimately, personal and public health in the future. Long-term sustainability of the FNS-Cloud will be based on Services that have the capacity to link with new resources and enable cross-talk amongst them; access to FNS-Cloud data will be open access, underpinned by FAIR principles (findable, accessible, interoperable and re-useable). FNS-Cloud will work closely with the proposed Food, Nutrition and Health Research Infrastructure (FNHRI) as well as METROFOOD-RI and other existing ESFRI RIs (e.g. ELIXIR, ECRIN) in which several FNS-Cloud Beneficiaries are involved directly.

Prostate Cancer (PCa) is the second leading cause of cancer, among men in Europe. There are currently major unmet needs in this field, such as insufficient knowledge on risk factors that contribute to PCa and on patient characteristics (including genetic profiles) that could facilitate patient stratification. Finally, there is lack of meaningful engagement of all key stakeholders, while the knowledge currently gained from clinical practice and real life data is not being fed back into PCa patients’ care pathways. There is thus a need for better definition of PCa across all stages, improved patient’s stratification at diagnosis, and standardisation of PCa-related outcomes based on real life data. PIONEER’s unique dual approach is to first identify critical evidence gaps in PCa by respected Key Opinion Leaders, and then embark on a research priority setting exercise that reflects the needs of all key stakeholders in PCa management. To achieve this, PIONEER has brought together comprehensive datasets that consists of the most relevant prostate clinical trials and registries, large epidemiological cohorts, electronic heath records, and real-life data from different European (and non-European) patient populations. These unique data sets will be integrated, standardised, harmonised and analysed using approaches that are built on our experience of similar previous IMI projects i.e EMIF, and eTRIKS, and analysed using a unique set of methodologies and advanced analytics methods (OMOP, eHS). PIONEER has already performed a first PCa research priority setting survey, where major stakeholders were asked to identify the current unmet needs in PCa. The five most important open questions will be used as pilot studies to verify PIONEER’s research framework. As such, PIONEER’s deliverables will be outcome-driven, value-based and patient-centric, and relevant to all key stakeholders, as they would have been meaningfully involved from the inception of the project.

Europe generates real world health data (RWD) that has the potential to inform the development and evaluation of medicines and medical devices. However, multiple barriers remain that limit the access, analysis, interpretation, and use of RWD, hampering its use. Additionally, the limited uptake of existing guidelines for the generation and use of real world evidence (RWE) adds complexity in the use of RWD to inform decision making. The GREG consortium will leverage the learnings of previous and ongoing key RWE initiatives to fill these gaps by generating, pilot-testing, and disseminating evidence-based guidance and tools for the use of RWE to inform the development and evaluation of medicines, medical devices, and combinations. To achieve these goals, we will work with key stakeholders to iteratively test and improve our guidance and tools, backed by case studies from previous successful and unsuccessful examples. We will engage with the most relevant European RWE initiatives and access the largest network of RWD partners in Europe, namely the European Health Data and Evidence Network (EHDEN) through our partner, the EHDEN Foundation. Additionally, we will provide multi-stakeholder gatherings (including patient and public representatives) to promote the dissemination, adoption, and implementation of RWE for decision-making in Europe. Our public and private partners will co-create use cases working closely with key regulatory and health technology experts in bespoke fora. These will be used initially to evaluate existing guidelines, and later to pilot-test the GREG guidance and tools. Our outputs will include training for all involved stakeholders on the use of our guidance and tools, and practical templates to facilitate regulatory and health technology/payer submissions. Together, these will accelerate access to better medicines and medical devices for European citizens.