The stated goal of RHAPSODY is to define a molecular taxonomy of type 2 diabetes mellitus (T2D) that will support patient segmentation, inform clinical trial design, and the establishment of regulatory paths for the adoption of novel strategies for diabetes prevention and treatment. To address these goals, RHAPSODY will bring together prominent European experts, including the leaders of the diabetes-relevant IMI1 projects to identify, validate and characterize causal biomarkers for T2D subtypes and progression. Our plans are built upon: (a) access to large European cohorts with comprehensive genetic analyses and rich longitudinal clinical and biochemical data and samples; (b) detailed multi-omic maps of key T2D-relevant tissues and organs; (c) large expertise in the development and use of novel genetic, epigenetic, biochemical and physiological experimental approaches; (d) the ability to combine existing and novel data sets through effective data federation and use of these datasets in systems biology approaches towards precision medicine; and (e) expertise in regulatory approval, health economics and patient engagement. These activities will lead to the discovery of novel biomarkers for improved T2D taxonomy, to support development of pharmaceutical activities, and for use in precision medicine to improve health in Europe and worldwide.

Diabetic kidney disease (DKD) is the leading cause of end stage renal disease (ESRD), and its global incidence and prevalence have reached epidemic dimensions in recent years. Unfortunately, there are no effective means to prevent or cure DKD, the few existing treatments have limited effect and very few alternative therapies have emerged in the past years. Lack of new predictive and prognostic biomarkers for a more accurate patient stratification, limited access to kidney tissue from patients at various stages of DKD as well as novel model systems to better understand the pathogenesis of the disease, are likely reasons for the stagnating development of new treatments. The BEAt-DKD consortium combines outstanding basic and translational researchers in nephropathy, diabetes, kidney model systems, imaging techniques and systems biology, and includes leaders of diabetes and kidney disease-relevant IMI1, FP7 and US consortia, like SUMMIT, KIDNEYCONNECT, Syskid, CPROBE and C-Path, in an unprecedented search for new and better biomarkers for DKD, through a better understanding of the disease. Jointly, the partners have access to vast and very relevant clinical cohorts and trials, state-of-the-art analysis and imaging techniques, novel model systems and the long-standing experience and networks to make this collaboration a success. By involving regulatory agencies throughout the project, BEAt-DKD aims at making the introduction and acceptance of new tools as efficient as possible. The overall goals of BEAt-DKD are (1) to provide a holistic systems medicine view of the pathogenesis of DKD with the aim to identify targetable mechanisms and pathways underlying initiation and progression of DKD, applying a novel sub-classification of diabetes, and (2) to identify and validate biomarkers of disease progression and treatment responses representing first steps towards precision medicine in the management of DKD.

The launch of a novel drug to the market is preceded by clinical testing and validation both on animal in vitro and in vivo models. Animal models used in drug development have known methodological drawbacks leading to the failure of drugs. Further, animal tests are associated with ethical issues. Moreover, a strong bias in in-human testing still overlooks major population groups e.g. children, women, different ethical groups. It is estimated that 197,000 deaths per year in the EU are caused by Adverse Drug Reactions (ADRs) and the total cost to society of ADRs is €79 billion. The emerging Organ-on-Chip (OOC) field, an alternative to animal test, brings great potential for safe testing and validation: An OOC-systems consists of a 3D-microstructured channel network embedded on a small plastic device that simulates the mechanics and physiological response of an entire organ or organs. Project UNLOOC will develop, optimize, and validate a multitude of ECS-based tools to build OOC-models to replace animal and in-human testing. UNLOOC aims to combine three important characteristics for routine use of OOC models, i.e platforms that combine ECS-based technologies with established biological material, capitalize on AI, parallelized test set-ups allowing efficient high-throughput demands, and standardized procedures enabling reliable results. UNLOOC will develop ECS-based hardware and software tools and validate them in five Use Cases (UCs) performed in 10 European countries. The applications developed and validated will be used by academia and pharma industry to drive drug development, create cosmetics without animal test, personalized medicine and gain new insights into disease. Given the large OOC market, these solutions have great economic value, on average it would result in cost reduction of up to $169M and $706M per new drug reaching the market and will put Europe at the forefront of this booming research field (see impact section for details).

Chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF) are two very debilitating non-communicable diseases that are of particular interest to consider in parallel in a human exposome study. Their roots are opposite: COPD is currently considered to be mainly related to the external exposome, while factors outside of the exposome play a major role in CF. However, COPD and CF share common characteristics such as high phenotypic variability of unknown origin, which prevents good therapeutic efficacy. It is therefore clear that the overall picture must be supplemented by taking into account additional components of the exposome than those currently considered in COPD and CF. Thus, the overall objective of the REMEDIA project is to extend the understanding of the contribution of the exposome, taken as a complex set of different components, to COPD and CF diseases. We will exploit data from existing cohorts and population registries in order to create a unified global database gathering phenotype and exposome information; we will develop a flexible individual sensor device combining environmental and biomarker toolkits; and use a versatile atmospheric simulation chamber to simulate the health effects of complex exposomes. We will use machine learning supervised analyses and causal inference models to identify relevant risk factors; and econometric and cost-effectiveness models to assess the costs, performance and cost-effectiveness of a selection of prevention strategies. The results will be used to develop guidelines to better predict disease risks and constitute the elements of the REMEDIA toolbox (global unified database, sensor device, versatile atmospheric simulation chamber, machine learning supervised analyses, causal inference model, Pan-European multi-criteria risk assessment tool, econometric models, cost-effectiveness models, new guidelines and recommendations). Deciphering the impact of environmental components throughout life on the phenotypic variability of COPD and CF could represent a major breakthrough in reducing morbidity and mortality associated with these two non-curable diseases and would lead to the identification of modifiable risk factors on which preventive action could be implemented. REMEDIA will be part of the European Human Exposome Network established between the 9 projects funded within the Human Exposome programme call H2020-SC1-BHC-2018-2020.

LysoMod will innovate in the area of personalized medicine for disorders linked to lysosomal dysfunction. This will be achieved by implementing a collaborative staff-exchange program between highly complementary and multidisciplinary academic and non-academic partners with expertise in pharmacology, medicinal chemistry, cell biology, biochemistry, mouse and human genetics, transcriptomics, proteomics and lipidomics. Based on the critical role that lysosomes play in cells, a better understanding of lysosomal function will have a major impact on human health, fostering the development of new strategies to improve quality of life for people affected by a variety of diseases, ranging from lysosomal storage diseases (LSDs) to age-related neurodegenerative disorders. LysoMod’s specific objectives are: 1) to develop and further optimize existing therapies for LSDs; 2) to identify new targets for personalized therapies for LSDs; and 3) to investigate the cross-talk between lysosomal function, signalling pathways and gene expression regulation. The pioneer work of a participant in the consortium led to the development of a drug that is approved for clinical use. LysoMod will i) investigate the mechanisms of action of this and other drugs in lysosome-related disorder; ii) identify modifier genes involved in LSD pathology and test their potential as new targets for personalized therapeutic approaches; iii) identify candidate RNAs that can be targeted to enhance lysosomal function. The companies in the consortium will ensure a rapid transfer of new knowledge into applications for diagnostics and clinical trials. Prioritising lysosomal dysfunction as a highly relevant biomedical problem, the LysoMod consortium will implement a mentored staff-exchange program to provide young researchers with high-level training in innovative approaches for exploring biological systems, preparing the next generation of researchers for careers either in the private or public health sectors.