Autoimmune disease affects 10% of adults, most of whom are women, and two of the top five medications with the highest cost globally are used to maintain these recurring conditions in remission. These medications act by suppressing the immune system, leaving the patient exposed to severe infection and at risk of cancer. Affected individuals receive standard treatment regimens for long periods of time, even though, in some cases, the autoimmune response may no longer be detectable. The general requirement for these medications, and their side effects, has been raised as a key target for research by the PARADISE consortium patient groups. Therefore, we aim to develop and validate a deployable personalised predictive tool that will accurately define the individual’s degree of immune system activation so that the medication dose can be tailored and, in some cases, stopped safely. We use systemic vasculitis as an archetypal autoimmune disease, integrating clinical, innovative biomarker and smartphone app-derived patient wellbeing data through a novel semantic web platform to inform predictive algorithms that will underpin a physician-facing tool. Such artificial intelligence (AI) applications are coming under intense scrutiny in the EU, so we will co-develop an “AI transparency notice” with the patient arm of the European Reference Network for immune disorders through a series of multi-stakeholder workshops, which will make explicit and explainable the full provenance of the PARADISE tool clinical outputs.

Europe’s Beating Cancer Plan set has ambitious goals addressing key behavioral risk factors for cancer development, such as tobacco (target reduction of 30% by 2025), alcohol consumption (target reduction of 10% by 2025), unhealthy diets and physical inactivity (see also the HealthyLifestyle4All campaign). As “about 40% of cancer cases in the EU are preventable”, health promotion and preventive measures for cancer can benefit from the implementation of behavioural change (BC) and emotional management (EM) in the general population. However, previous research and practice have generally failed to achieve sustainable BC due to two factors: 1) not taking into account recent BC concepts showing the need of personalizing interventions and techniques; 2) not considering psychosocial features and emotions (e.g. anxiety and depression), which can interfere with effective BC and increase the risk of developing cancer. The main objective of this project is to design, develop, and test the iBeChange platform, a user-focused management system that empowers people to achieve healthy and sustainable behaviors and emotions. The iBeChange innovative system will be developed by experts from clinical and health psychology, oncology, epidemiology, ICT, data science, and the health policy. The iBeChange project will go beyond the state of the art of sustainable BC and EM by combining practice- and evidence-based knowledge coming from clinical psychology and BC theories with the potentialities of adaptive digital technologies and artificial intelligence. Thus, the iBeChange system will be able to dynamically observe, learn about user behaviours, and then deliver tailored and effective health interventions in a dynamic learning process. The final goal of the iBeChnage project is to contribute to the goals of Europe’s Beating Cancer Plan and European Code Against Cancer by improving long-term primary cancer prevention through informing, supporting, and empowering EU citizens. This action is part of the Cancer Mission cluster of projects on "Prevention & early detection (behavioural change)".

ASSESS-DHT will increase the adoption of trustworthy and effective Digital Health Technologies (DHT) across Europe, enabling a more coherent digital single market, for health systems and patients to access DHT from all over Europe and giving industry a European market. We will develop a new assessment framework, beyond the existing models, capable of uniform HTA adoption across Europe, addressing new assessment challenges in Digital Therapeutics, AI and telehealth. Our consortium comprises 4 HTA bodies, the European Observatory on Health Systems and Policies, 5 academic and not for profit organisations with expertise in EU Regulation, DHT development and assessment methodologies, data protection, data quality, interoperability and cybersecurity. Patients and health professionals are included through the International Diabetes Federation and European Society of Cardiology. We include the DHT industry through companies with products for us to assess through a formal methodology mimicking actual HTA assessments – 3 as partners, some through an open call and industry-wide consultation via DIGITAL EUROPE. We will engage healthcare payers and ministries through our Advisory Board. We will co-create our overarching assessment framework with specialised pathways for different categories of DHT specified through a novel evidence-based typology. We will cater for phased adoption (going beyond fast track models like DiGA), complex life-cycles, iteratively developed AI, consolidated in a comprehensive HTA assessment manual plus specific guides in topics like cybersecurity. We will develop a sustainable repository containing the ASSESS-DHT framework, pathways and unambiguous criteria, a semantically searchable evidence library, checklists and tools to support companies with evidence generation, evidence of health system value from DHT, and online communities of practice.

Due to population ageing and advances in medical science, people with chronic diseases –including advanced severe life-threatening chronic diseases- live longer. Challenges are how to sustain quality independent living for the patient; support caregivers facing an increasing burden; create sustainable healthcare and social care systems with limited resources. ADLIFE aims to provide a solution for the integration of therapies and approaches targeting early detection and assessment of deterioration, advanced and well-coordinated care planning and integrated supportive care to enhance quality of life, reduce suffering and accelerate recovery for these patients and their families. It will deploy developed and validated personalised digital solutions for integrated supportive care based on H2020 projects C3-Cloud and Power2DM, previously tested in two health systems. The ADLIFE Toolbox solutions include: a Personalised Care Plan Management Platform, Clinical Decision Support Services; Interoperability Solutions and Patient Empowerment Platform with Just-In Time Adaptive Intervention Delivery Engine. The ADLIFE system will be deployed through large-scale pilots in 7 countries and Health Systems, involve 577 healthcare professionals from 75 hospitals, clinics and primary care services. It will prove that intelligent, collaborative digital solutions can enable care teams, patients and caregivers to improve or better maintain health in patients with advanced chronic disease (over 200,000 in the participating regions). It will test its effectiveness in 882 patients and 1243 caregivers. ADLIFE will demonstrate significant outcomes-based efficiency gains in health and care delivery enhancing seamless care coordination, avoiding gaps and overlaps in care. The ADLIFE ICT Toolbox and the evidence behind this digitally-enabled approach from the 7 reference sites will be strongly disseminated to multiple stakeholders and decision makers in Europe both online and in-person actions

Integrated, high-quality personal health data (PHD) represents a potential wealth of knowledge for healthcare systems, but there is no reliable conduit for this data to become interoperable, AI-ready and reuse-ready at scale across institutions, at national and EU level. AIDAVA will fill this gap by prototyping and testing an AI-powered, virtual assistant maximizing automation of data curation & publishing of unstructured and structured, heterogeneous data. The assistant includes a backend with a library of AI-based data curation tools and a frontend based on human-AI interaction modules that will help users when automation is not possible, while adapting to users? preferences. The interdisciplinary team of the consortium will develop and test two versions of this virtual assistant with hospitals and emerging personal data intermediaries, around breast cancer patient registries and longitudinal health records for cardio-vascular patients, in three languages. The team will work around four technology pillars: 1) automation of quality enhancement and FAIRification of collected health data, in compliance with EU data privacy; 2) knowledge graphs with ontology-based standards as universal representation, to increase interoperability and portability; 3) deep learning for information extraction from narrative content; and 4) AI-generated explanations during the process to increase users? confidence. By increasing automation of data quality enhancement, AIDAVA will decrease the workload of clinical data stewards; by providing high-quality data, AIDAVA will improve the effectiveness of clinical care and support clinical research. In the long-term, AIDAVA has the potential to democratise participation in data curation & publishing by citizens/patients leading to overall savings in health care costs (through disease prevention, early diagnosis, personalized medicine) and supporting delivery of the European Health Data Space.