The recent global burden of disease study showed that low back pain (LBP) is the most significant contributor to disability in Europe. Most patients seen in primary care with LBP have non-specific LBP (≥85%), i.e., pain that cannot reliably be attributed to a specific disease/pathology. LBP is the fourth most common diagnosis seen in primary care (after upper respiratory infection, hypertension, and coughing). Self-management in the form of physical activity and strength/stretching exercises constitutes the core component in the management of non-specific LBP; however, adherence to self-management challenging due to lack of feedback and reinforcement. This project aims to develop a decision support system - SELFBACK - that will be used by the patient him/herself to facilitate, improve and reinforce self-management of LBP. Specifically, SELFBACK will be designed to assist the patient in deciding and reinforcing the appropriate actions to manage own LBP after consulting a health care professional in primary care. The decision support will be conveyed to the patient via a smartphone app in the form of advice for self-management. The advice will be tailored to each patient based on the symptom state, symptom progression, the patients goal-setting, and a range of patient characteristics including information from a physical activity-detecting wristband worn by the patient. The second part of the project will evaluate the effectiveness of SELFBACK in a randomized controlled trial using pain-related disability as primary outcome. We envisage that patients who use SELFBACK will have 20% reduction in pain-related disability at 9 months follow-up compared to patients receiving treatment as usual. Process evaluation will be carried out as an integrated part of the trial to document the implementation and map the patients’ satisfaction with SELFBACK. A business plan with a targeted commercialisation strategy will be developed to transfer the SELFBACK technology into the market.

The current animal-based testing of materials’ short- and long-term health effects is slow, expensive, and has limited capacity, which stifles the development of new (nano)materials and hinders efficient regulation of the market. To enable cost-efficient high-throughput screening required for industry and regulation, we here propose to shift the focus of nanosafety testing from late endpoints to early key events (KEs) leading to adverse outcomes (AOs). As such tests can only be based on mechanistic understanding, we need to close the knowledge gaps and match KEs in vitro and in vivo, which the nanoPASS consortium is in a unique position to provide. Our key bridging methods are intravital in vivo microscopy, quantitative time-lapse in vitro microscopies, and automated identification of the modes of action (i.e. KE relationships) with proprietary in silico algorithms, supported by datamining of the worlds’ largest in vivo database and single-cell omics data, and computational modelling of structure-function relationships. With this toolset, we aim to 1) develop new in vitro systems that can replicate early KEs leading to AOs related to inhalation of NMs, 2) identify methods to track the dynamics of these KEs, 3) develop quantitative in silico models to predict AOs, and 4) calibrate the in vitro/in silico AO predictions against in vivo data for 40+ well-characterised benchmark materials. Finally, we will 5) validate the AO predictions on several families of industrial materials, sampled from different stages of their life cycle, and then propose reliable testing protocols and guidelines to OECD and ECVAM. With the consortium of 6 complementary research laboratories, SME as technology developer and provider, material producing company as potential end-user, and an industrial association to facilitate dissemination, nanoPASS covers the whole value chain of the new animal-free safety testing technology, and thus paves the way towards safe adoption of new nanotechnologies.

In a large majority of non-communicable diseases (NCDs), including the immune-mediated diseases (IMDs), complex gene-environmental interactions contribute to the onset and development of disease through the modulation of biological pathways. IMDs are characterized by abnormal immune responses, have limited therapeutic options and require lifelong treatment if not detected during the preclinical stage. EXPOSIM will provide a strong evidence base to better understand the impact of combined environmental stressors on immune health, with a focus on air pollution, noise and hazardous waste in urban areas. More specifically, we will investigate the impact of environmental stressors – the external exposome – on IMDs and immune health at different stages in life (pregnancy, childhood and adulthood). We will identify biological pathways and molecular mechanisms mediating the effect of combined exposures on IMDs. Through case studies and topical reviews, we will demonstrate the effectiveness of exposure-reducing and health-promoting interventions, with a focus on vulnerable and highly exposed individuals. This knowledge will be translated into policy recommendations and informed decision-support tools. Moreover, the project emphasises on scientific collaborations and stakeholder engagement, involving co-creation of health-promoting actions, education, training and communication. EXPOSIM will build a user-friendly toolbox for regional, national and EU policymakers, health professionals, researchers and citizens. To reach its ambitious objectives, EXPOSIM brings together a geographically balanced, experienced interdisciplinary consortium (active in PARC, EXIMIOUS, EHEN, METEOR) of ten European partners with complementary expertise in exposome research, epidemiology, immunology, omics, novel data analytics, health economics and social sciences and humanities. Ultimately, EXPOSIM will contribute to a healthy environment and healthy lives for all EU citizens.