Cross-border collaboration can tackle the challenges in accessing relevant health data essential for international collaboration between scientists and clinicians, researchers, and health industry. Privacy concerns and regulations on personal data have made the sharing of health data increasingly complex and time-consuming for data controllers, thus severely limiting the access of SMEs, researchers, and innovators to health data. Further complications in cross-border collaboration arise from differences in interpreting the EU GDPR, national regulations, and heterogenous and changing data permit processes at hospital sites. The PHEMS project will provide European children’s hospitals with a decentralized and open health data ecosystem concept consisting of technical components and governance frameworks. The objective is to facilitate access to health data, advance federated health data analysis and build services for the on-demand generation of shareable, synthetized, and anonymized datasets. To achieve this, the project will focus on bridging the gaps in data access and use, especially in the integration of ethical, legal, and technical requirements, including the responsibilities of data controllers and the rights of data subjects. This will allow health data controllers to engage in collaboration without losing control on compliance with respect to GDPR, national legislation or internal policies of their organization. The techniques and tools for generating algorithmically anonymized and synthetic datasets will undergo robust validation processes through three clinical use cases conducted by the European Children’s Hospitals Organisation (ECHO) community. The goal is to assess the usage of custom-generated synthetic data with real-life questions. Data users, such as researchers, SMEs, innovators and the pharmaceutical and MedTech industry, will be engaged through community building, hackathons, and interaction with relevant European large-scale initiatives.
Successful drug approvals on Precision Oncology (PO) using basket studies have uncovered new challenges. Research in small patient populations suffers from sustainability/ logistical issues. Platform trials are flexible solutions to test different drugs in different populations but encompass management issues that compromise flow and translational research. This is detrimental to patients/ researchers thus new technological/ methodological concepts must be urgently implemented. To overcome these limitations, Cancer Core Europe (CCE) has developed the Basket of Basket (BoB) study to provide personalized treatment to a larger number of patients by incorporating a multi-tiered molecular profiling platform, flexible modules targeting different molecular alterations and a data/ sample collection plan to enable translational research. The CCE-DART model, here proposed, is conceived to address other limitations of PO and platform trials identified by our multi-disciplinary team. With a new design, we aim to improve efficiencies and transform platform trials in data-rich translational research programs, by: (1) developing digital systems (information-technology solutions) facilitating data management and clinical-decision-making; (2) integrating accurate, dynamic imaging and molecular markers of tumor progression/ drug response; (3) using more efficient, adaptive clinical trial methodology; (4) increasing patient engagement. To achieve this, we will use harmonized data-sharing/ technological/ legal/ clinical infrastructure developed in CCE and the BoB trial that will be leveraged as a use case for testing the new model. The new concept will impact the design of new clinical trials consolidating a self-sustainable, data-rich, multi-endpoint global platform for clinical/ translational research, encompassed by a pharmacoeconomics assessment that will proof the sustainability of the model for its implementation in the Health System and as a return of the investment to society.
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.
The mission of AiPBAND is to train a new generation of entrepreneurial and innovative early-stage researchers (ESRs) in the early diagnosis of brain tumours using molecular biomarkers in the blood, meeting the medical and societal challenges of this emerging field. AiPBAND will focus on gliomas, a range of devastating and progressive brain tumours affecting around 25,000 people each year in Europe and responsible for the majority of deaths from primary brain tumours. Fourteen fellows will be trained by experts in 9 academic and 3 non-academic beneficiaries, belonging to 5 EU member states and 6 partner organizations (4 private sectors and 2 international academic), with fields ranging from neuroscience, engineering (including big data science), healthcare to economics. State-of-the-art technologies will be applied in parallel to (i) identify novel blood biomarkers from patients with gliomas, (ii) design three types of multiplex biosensor (plasmonic-based, graphene-based, and digital ELISA assay-based), (iii) develop a big data-empowered intelligent data management infrastructure, and (iv) develop cloud-based diagnostic systems. Proof-of-concept will be evaluated through clinical trials to assess accuracy, sensitivity and specificity. The elaborately designed individual research projects under the Vitae Researcher Development Framework – carefully arranged into local training courses, network wide events, secondments, personalized career development plans, with strong involvement of the private sector – will ensure exploitation of AiPBAND's achievements, and will maximize the ESRs’ abilities in creative & innovative thinking, triple-i knowledge transformation, and encourage a business-orientated mind-set and entrepreneurship.