The European manufacturing industry faces new challenges, which are currently not addressed by today’s products and systems. Most of the products are still in essence ‘simple’ in nature, with no capability for adapting to the consumers’ needs and no integrated methods exist for the holistic acquisition and processing of feedback information emanating from product-services. ICP4Life proposes an integrated, collaborative platform for the design, development and support of product-service systems for SMEs, equipment manufacturers and energy suppliers in order to maximize the impact in the European industry. The proposed platform comprises of three main components. The first component demonstrates a collaborative web-based application for the creation and management of products and services by engineers and designers of multiple disciplines. The second component is a Product-Service configuration tool for customers, enabling the easy and intuitive formation of Products and Services. The same component will be used for managing product related data pertaining to the manufacturer, supplier and the customer. The third component will support the efficient, adaptive and responsive planning and decision making phases, for managing the dynamic operation of the plants and the supply chain. All the components will be compatible with open standards, such as AutomationML, in order to make the most out of and accelerate the adoption by the European industry. The ICP4Life project will address the current needs of today’s manufacturers, providing faster design of modular equipment and components, the seamless collaboration of engineers across a wider network of companies as well as within a single company with disperse engineering offices and production sites and the reuse of knowledge regarding both products and processes for new projects or the configuration of existing lines. The ICP4Life consortium consists of highly skilled organizations to ensure the success of this project.

With Colorectal Cancer (CRC) being accountable for 12.4% of all deaths due to cancer, and with only 14% of EU citizens participating in screening programmes, there is an urgent need for accurate, non-invasive, cost-effective screening tests based on novel technologies and an increased awareness on the disease and its detection. Furthermore, personalized approaches for screening are needed, to consider genetic and other socioeconomic variables and environmental stressors that lead to different onsets of the disease. ONCOSCREEN responds to these challenges by developing a risk-based, population-level stratification methodology for CRC, to account for genetic prevalence, socio-economic status, and other factors. It complements this methodology by a) developing a set of novel, practical, and low-cost screening technologies with high sensitivity and specificity, b) leveraging AI to improve existing methodologies for CRC screening, allowing for the early detection of polyps and provision of a personalized risk status stratification, and c) providing a mobile app for self-monitoring and CRC awareness raising. Furthermore, ONCOSCREEN develops an Intelligent Analytics dashboard for policy makers facilitating effective policy making at regional and national levels. Through a multi-level campaign, the above-mentioned solutions are tested and validated. For the clinical solutions specifically, a clinical validation study has been planned with the participation of 4100 enrolled patients/citizens. To ensure the adoption of the developed solutions by the healthcare systems, their cost-effectiveness and financial viability will be assessed. The 48-months duration project will be implemented by a multidisciplinary consortium comprising of 38 partners, including technical solutions providers, hospitals, Ministries of Health as policy makers, legal and ethics experts, Insurance companies, involving actively end-users/citizens in all phases of implementation through targeted workshops. This action is part of the Cancer Mission cluster of projects on ‘Prevention, including Screening.

Manufacturing and logistics companies are subject to unforeseen events that disrupt the supply chain, causing production slowdowns, reduced output, and increased costs, making it difficult to meet customer demand. To mitigate these risks, manufacturers must build resilience across entire value chains. NARRATE will develop a sophisticated tool using AI, Digital Twin, and IoT technologies allowing end-to-end visibility and control over supply chain operations to monitor and predict potential disruptions, enabling supply chains to achieve improved resilience. The Intelligent Manufacturing Custodian (IMC) will leverage data from various production sources to enable proactive decision-making and act as a nerve centre for a supply-chain network, providing real-time monitoring and coordination of intelligent production processes and logistics. Integrating an IMC into a supply-chain will evolve its operations into Smart Manufacturing Network (SMN): a connected and self-orchestrated ecosystem linked end-to-end with programmable Manufacturing-as-a-Service capabilities that can withstand disruptions. A Digital Twin will provide a reliable model to represent production and operational data of an SMN to unlock deeper IMC intelligence. Collected data will train machine learning models to predict potential disruptions, such as natural disasters or delayed shipments. AI algorithms will analyse the data and provide real-time reporting and visualization on a dashboard. The IMC and Digital Twin interaction will generate powerful insights and self-adapting abilities that support an SMN to evolve under human supervision by switching services between multiple external partners to respond to risks and disruptions and improve energy efficiency, product circularity and environmental sustainability across the entire production process. The effectiveness of NARRATE will be evaluated by testing the IMC in real production environments in quite diverse industry sectors.

Cancer immunotherapy brought about significant progress in cancer treatment. It resulted in high efficacy in some cancers; e.g., up to 60% objective response rate in melanoma and 80% complete response rate in acute lymphoblastic leukaemia. Nevertheless, two main challenges still impede improving cancer patients’ health status and quality of life (QoL) after immunotherapy initiation: 1) a crucial need for “predictive markers” of occurrence of immunotherapy-related adverse events (IR-AEs) to predict and improve patients’ health status and promote their QoL; and, 2) the lack of knowledge on patients after start of immunotherapy outside randomised controlled trials. To reach these goals, significantly more diversified sources of data are required. Project QUALITOP aims at developing a European immunotherapy-specific open Smart Digital Platform and using big data analysis, artificial intelligence, and simulation modelling approaches. This will enable collecting and aggregating efficiently real-world data to monitor health status and QoL of cancer patients given immunotherapy. Through causal inference analyses, QUALITOP will identify the determinants of health status regarding IR-AEs and define patient profiles in a real-world context. For this, heterogeneous data sources (big data), both retrospective and prospective --collected for QUALITOP from clinical centres in four EU countries—will integrate lifestyle, genetic, and psychosocial determinants of QoL. Using machine learning approaches, QUALITOP will provide "real-time" recommendations stemming from patient profiles and feedbacks via the Smart Digital Platform. Furthermore, an increased visibility on patients’ behaviour, a better IR-AEs prediction, and an improvement of care coordination will help analysing through simulation modelling approaches the gain in cost-effectiveness. Guidelines will be issued over the short and long-term.