Medicines play a crucially beneficial role in society, and their importance and use are expected to increase due to the expanding and aging world population. However, the increased use of medicines also heightens the environmental exposure, stressing the eco-system and adversely impacting our long-term health, as exemplified by reproductive disorders by drug residues in the environment and resistance to antibiotics. Moreover, socio-economic equality towards medicines is a global challenge. There is thus a need for a global systematic approach, followed by competent authorities as well as academic, civil and industrial organisations, to take into account sustainability over the entire life cycle of a medicine. Indeed, emphasis should also be paid to sustainability from the “cradle”, i.e. in the drug discovery phase, rather than only at the later stages of product development or clinical stages (the “grave”), in line with tackling the root cause as recommended in 6-sigma lean philosophy.In this International Master of Sciences in Sustainable Drug Discovery (S-DISCO), a unique, transdisciplinary programme is developed, covering a broad range of selected pharmaceutical disciplines, focused on the early discovery phases and intertwined with environmental and socio-economic topics. It is jointly delivered by 4 complementary European universities (i.e. Ghent University, University of Lille, Medical University of Gdansk and University of Groningen) and supported by international experts from industry and relevant (academic) institutions to assure a unique, worldwide excellence and attractiveness. A clear mobility track is proposed, giving the students the opportunity to study and gain specific expertise at the different partner universities.

Breast cancer is now the most common cancer worldwide, surpassing lung cancer in 2020 for the first time. It is responsible for almost 30% of all cancers in women and current trends show its increasing incidence. Neoadjuvant chemotherapy (NAC) has shown promise in reducing mortality for advanced cases, but the therapy is associated with a high rate of over-treatment, as well as with significant side effects for the patients. For predicting NAC respondents and improving patient selection, artificial intelligence (AI) approaches based on radiomics have shown promising preclinical evidence, but existing studies have mostly focused on evaluating model accuracy, all-too-often in homogeneous populations. RadioVal is the first multi-centre, multi-continental and multi-faceted clinical validation of radiomics-driven estimation of NAC response in breast cancer. The project builds on the repositories, tools and results of five EU-funded projects from the AI for Health Imaging (AI4HI) Network, including a large multi-centre cancer imaging dataset on NAC treatment in breast cancer. To test applicability as well as transferability, the validation with take place in eight clinical centres from three high-income EU countries (Sweden, Austria, Spain), two emerging EU countries (Poland, Croatia), and three countries from South America (Argentina), North Africa (Egypt) and Eurasia (Turkey). RadioVal will develop a comprehensive and standardised methodological framework for multi-faceted radiomics evaluation based on the FUTURE-AI Guidelines, to assess Fairness, Universality, Traceability, Usability, Robustness and Explainability. Furthermore, the project will introduce new tools to enable transparent and continuous evaluation and monitoring of the radiomics tools over time. The RadioVal study will be implemented through a multi-stakeholder approach, taking into account clinical and healthcare needs, as well as socio-ethical and regulatory requirements from day one.

Neurofibromatosis type 1 (NF1), NF2 and non-NF2 schwannomatosis (SWN) belong to the NF disease spectrum. Legius syndrome (LGSS) and Constitutional Mismatch Repair Deficiency (CMMRD) are both differential diagnoses of NF1. These five syndromes are rare, genetically and clinically distinct diseases with variable course, however the majority present with severe complications and tumor development. The life expectancy is mainly improved by early diagnosis and personalized medical care in a specialized reference center. A large percentage of these patients currently remain without a genetic diagnosis, although their clinical features strongly suggest the presence of a still unknown genetic cause. The main objective is to expand the availability and access of validated diagnostic and functional tools among the consortium members and other laboratories to maximize the genetic diagnostic yield for patients with NF-SWN and related disorders. Firstly, we will develop, validate and compare new DNA and RNA-based testing techniques to improve genetic diagnosis. Secondly, we want to test the pathogenic effect of variants of unknown significance on RNA level and by using functional assays and iPSCs. Thirdly, we will retest NF1-, LGSS-, NF2- and SWN-like patients with negative genetic diagnosis using newly developed RNA and DNA molecular techniques. Lastly, C4CMMRD consensus criteria will be evaluated. We expect to share new sensitive and specific diagnostic assays and bioinformatics tools that can be globally used to characterize molecularly patients with NF-SWN-LGSS and CMMRD and to identify new candidate genes. A worldwide accurate molecular diagnosis for patients with NF-SWN and related disorders will greatly impact the financial and clinical outcome as well as the therapeutic options, quality of life and societal burden.

MAYA addresses the third intervention outlined in the call by developing, testing, and scaling up innovative, holistic approaches and tools for managing late effects of cancer treatment in AYA cancer (of any type) survivors. MAYA aims to empower Adolescents and Young Adults (AYA) cancer survivors to manage their cardiovascular (CV) health through digital tools that address cardiotoxic-related late effects of cancer treatment. The project envisions using the iCARE health hub, which integrates a smart mirror and an AI-powered conversational agent, to deliver personalised care and continuous monitoring. The ultimate goal is to improve cardiovascular outcomes and overall quality of life for AYA survivors by managing modifiable risk factors such as hypertension, diabetes, and obesity, with an expected reduction in the risk of major cardiac events by 30-40%. MAYA will achieve these objectives through advanced AI-driven data analysis, real-time biomarker tracking, and participatory research methods including social innovation, multistakeholder engagement, and Living Labs. The project will test these solutions in real-world settings through clinical studies involving AYA cancer survivors in multiple European countries. By focusing on personalised interventions and continuous health monitoring, MAYA directly aligns with the objectives of the Horizon Europe work programme, particularly the Cancer Mission's goals of improving long-term health outcomes and quality of life for cancer survivors. Additionally, the project contributes to the work programme’s emphasis on innovation in healthcare and equity across diverse healthcare systems. This action is part of the Cancer Mission cluster of projects on “Quality of life (AYA).