The goal of EuCanImage is to build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of artificial intelligence (AI) in oncology. Firstly, the EuCanImage platform will be populated with a completely new data resource totaling over 25,000 single subjects, which will allow to investigate unmet clinical needs like never before, such as for the detection of small liver lesions and metastases of colorectal cancer, or for estimating molecular subtypes of breast tumours and pathological complete response. Secondly, the cancer imaging platform, built by leveraging the well-established Euro-Bioimaging infrastructure, will be cross-linked to biological and health repositories through the European Genome-phenome Archive, allowing to develop multi-scale AI solutions that integrate organ-level, molecular and other clinical predictors into dense patient-specific cancer fingerprints. To deliver this platform, the consortium will build upon several key European initiatives in data sharing for personalised medicine research, including EUCANCAn (cancer genomics and health data sharing), euCanSHare (cardiac imaging and omics data sharing) and EUCAN-Connect (federated data analytics). Furthermore, to foster international cooperation and leverage existing success stories, the consortium comprises the coordinators of The Cancer Imaging Archive (TCIA), the US cancer imaging repository funded by the National Cancer Institute. This will allow EuCanImage to leverage a unique 10-year long experience in cancer imaging storage, anonymisation, curation and management. Finally, a close collaboration between world renown clinical, radiomics, AI and legal experts within the consortium and beyond will establish well-needed guidelines for AI development and validation named FUTURE, for delivering Fair, Universal, Traceable, Usable, Robust and Explainable decision support systems for future cancer care.

Most cases of gastric cancer (GC) are detected at a late stage, when patients have a median life expectancy of about a year. Diagnosing people at risk of developing GC at the pre-symptomatic stage, typically chronic gastric inflammation, could significantly improve the outlook. Artificial intelligence (AI) can help clinicians make sense of their own data by automating much of the treatment and analysis, which require manual work and years of experience. But it can do more: it can bring together available data from various sources into a vast data lake and cross-correlate the data to derive a ‘risk score’ for gastric cancer and shed light on the mechanisms of its evolution. Aida aims to do just that. It helps researchers understand the mechanisms that trigger gastric oncogenesis, helps clinicians diagnose precancerous inflammation at the earliest possible stage, suggests personalised therapeutic strategies for treatment and follow-up, and makes personalised recommendations for monitoring patient health status, thus contributing to gastric cancer prevention. This places Aida squarely on Europe’s agenda of ‘Staying healthy in a rapidly changing society’. Aida unites some of Europe’s leading authorities in the field of gastric inflammation, gastric cancer, leading AI and machine learning experts, experts on data governance and privacy, representatives of the public administration and patient advocates. Aida also has strong ties with the industry. After the project, the results will live on in an association that acts as a transnational focal point for chronic gastric inflammation — and GC in general. We hope that the solid, inclusive design principles of Aida, its societal relevance and its durability will spawn a vigorous ecosystem around chronic gastric inflammation, its understanding and its treatment. And we hope that it will inspire other data collaboratives in health — for other chronic inflammations, other forms of cancer or other ailments altogether.

Female breast cancer is the most diagnosed cancer worldwide. In 2020, the International Agency for Research on Cancer estimated more than 2.26 million new cases of breast cancer. Early detection is crucial to survival; recovery rates approach 90% when detected in early stages. National population-based cancer screening programmes in Europe currently implement 3 standard imaging modalities: mammography, ultrasound and MRI. The downsides of these screening methods include ionising radiation, high costs and high false positive rates in screening results. Our multidisciplinary consortium of 16 partners from 10 countries aims to contribute to EU’s Mission on Cancer and Beating Cancer Plan by drastically improving the prevention, diagnosis and monitoring of breast cancer while reducing the burden on women and female patients and their families, health care professionals and others who are directly or indirectly affected by breast cancer. ThermoBreast proposes a new solution for accurate, harmless and non-contact screening, equally applicable for all age groups and breast densities and capable of detecting pre-cancerous states. This risk-free screening technology, recently patented by the project coordinator ThermoMind LTD, can detect vascular anomalies and asymmetry, caused by cancerous growth. It combines innovative screening through multiple sensitive infrared sensors with advanced AI analysis of temporal dynamic thermal patterns. Through its patient-centred integrated diagnostics approach, this project converges intelligent computer vision, blood vessel extraction and tissue analysis with advanced information technology to deliver a medical class 1 device that will be validated in an international multicentre clinical study. To enhance stakeholder participation, ThermoBreast involves end users, SSH experts and a patient organisation in the co-creation of the new screening solution and assesses its health and socio-economic benefits as well as its cost effectiveness. This action is part of the Cancer Mission cluster of projects on ‘Prevention, including Screening’.

In IMPACT-AML, a multidisciplinar R/R AML represents a model of high-impact disease, in which no standard of care exists, and where we have an urgent need for new evidence on possible therapies; AML offers the setting in which methodological innovation will combine powerful instruments of clinical trials with personalized medicine through academic efforts. Hereby, we propose to create an inclusive master framework for relapsed or refractory acute myeloid leukemia (STREAM) to include patients with R/R AML across Europe proficiently acquire an unselected population for clinical trials and monitor outcomes including neglected cohorts. Thereafter we will conduct a prospective randomized pragmatic clinical trial (RPCT) that will compare the classical “high intensity” rescue chemotherapy with biology-driven, “low intensity” rescue to obtain “real world” data on the benefit of one of the two different strategies in term of survival also considering patients and caregivers preferences, patient-reported outcomes (PRO), accessibility, affordability, and social cost. RPCT will aim to evaluate the effectiveness of real-world clinical alternatives in routine care. In addition to retaining the high internal validity of traditional randomized trials, it will maximize external validity, i. e. generalizability of results to many settings. In this context, the inclusion of an RPCT in the master framework will allow a dynamic inclusion and the collection of the excluded population as an instrument to predict the real-life applicability of clinical trial results. We will offer Europe results from an ambitious project, that will go beyond the state of the art in R/R AML demonstrating the superiority of a strategy in a first-of-his-kind clinical trial, providing strong data that will be delivered to national health care providers, policymakers, and health authorities data on optimized and affordable treatment for R/R AML and promoting the implementation of the selected better option. This action is part of the Cancer Mission cluster of projects on ‘Diagnosis and treatment’.

There is a growing recognition that health and wellness apps need to play a much stronger role in health care systems, self-care and health prevention than they do today. However, health care systems, health professionals, patients and citizens lack means to adequately assess the quality and reliability of the many apps to choose from, for every purpose, in each app store. Suppliers experience the varying national approval processes as confusing and unclear as to what is expected and the depth of evidence that is required by each approval body. We intend to break through the impasse by leveraging the golden opportunity of the publication in July 2021 of the ISO 82304?2 Technical Specification (TS) and its health app quality label. Work is now needed to turn this globally endorsed quality assessment and health app quality label into the EU assessment and EU mHealth label, embed it within the approval and reimbursement processes of European countries and foster cross-country alignment of these approval processes. The objective of Label2Enable is threefold: achieve trust, use and adoption. We will pursue: 1. trust with an EU certification scheme that results in consistent compliant inclusive app assessments 2. use with: - a more detailed health app quality report that enables health professionals to recommend apps and insurers to speed up decisions on reimbursements - supporting communication that enables all patients, citizens and carers to use the label in considering health apps - social experimentation to promote app stores, app libraries and other routinely used trusted sources that (seek to) offer health apps to effectively publish the label alongside them 3. adoption of the TS and cross-country recognition with pilots, use stories, advocacy, mass communication and targeted multi-stakeholder engagement, affordable app assessments and a sustainable non-profit entity that will maintain the scheme, accredit app assessors and promote the TS after the project.