The vision of MODALSHIFT lies in the creation of a transport network and traffic management optimisation framework, trusted and valuable for local stakeholders, that bridges the data from infrastructures, logistics and mobility operators. New IoT devices - a smart box enabling Capacity-as-a-Service, and a e-subscription device for public transport access for vulnerable people, will increase the sources for data collection. A mobility data space, associated to novel geolocation data anonymisation, will be set up in the 3 Case Studies (Bulgaria, Italy, Spain) to ensure trusted and secure data exchange between data providers and users. This multisource data will enhance traffic state forecasting and increase the detection rate of events by 15%. On this basis, predictive and prescriptive analytics and synchromodality-based scenarios, tested in digital twins and early pilots, will identify optimal actions of transport stakeholders for adjusting their operations, towards a reduction of 25% of the interconnection or transshipment delays. Agent-based modelling will identify how a modal shift towards low-carbon, active and shared mobility services can be acceptable by end-users and support a reshape of the public transport services and the use of urban space. A multimodal traffic management platform will orchestrate, upon the data space, the cooperation of stakeholders at network and multimodal hub scales. It enables the connection of dynamic optimisation algorithms to operational drivers’ tool for mobility operators, and of static models to visual interface for transport planners. The determination of governance models, values for each stakeholder, dynamic pricing and business models, will steer the participation of 8 stakeholders for each Case Study in the multimodal traffic management system. With this approach, MODALSHIFT stimulates new uses of the transport network to reduce traffic congestion for low-carbon and inclusive mobility, avoiding pernicious rebound effects.

Parkinson’s Disease (PD) is a major neurodegenerative disorder with no established treatment modalities capable of modifying disease pathology, and no means of early diagnosis. Vaccines targeting aSyn aggregates are a promising route to disease-modifying therapy for PD, but the current generation of PD vaccines utilise conventional formulations, which are limited in their immunogenicity and require substantial quantities of adjuvant to achieve efficacy. NEXGEN’s proprietary WISIT vaccine platform is the first of the novel class of gluconeoconjugate vaccines (GNCVs), which are administered intradermally and specifically formulated to leverage skin dendritic cells (DCs) to generate substantially stronger and more specific immune responses than conventional vaccines. These stronger immune responses allow substantial reduction in adjuvants, while simultaneously increasing therapy efficacy. NEXGEN will identify and characterise candidate WISIT constructs targeting aSyn (PD-WISITs) and develop a novel extracellular vesicle (EV)-based biomarker assay that enables early diagnosis of PD using liquid biopsies, suitable for point of care use. Safety and efficacy of PD-WISITs will be demonstrated preclinically, before being translated to first-in-human Phase I/Ib clinical trials, along with the novel EV-based biomarker assay. The results of NEXGEN will be the extraordinary accomplishments of cheap and effective disease-modifying treatment of early PD and a novel biomarker assay to diagnose and guide prodromal/early PD treatment. Further still, GNCV technology will be clinically demonstrated, which has the potential to be transformative to the treatment of a wide range of additional diseases, resulting in far-reaching impacts to the health of millions.

New technologies in transport enabled systems with the capacity to improve safety, efficiency, sustainability and comfort. Advances in vehicle automation allow the circulation of vehicles with a minimal human intervention in the near future. However, this irruption brings new technical and non-technical challenges that are to be addressed to ensure safe adoption of level 3 automated vehicles. Based on existing prototypes of automated vehicles (provided by the consortium), will perform multidisciplinary research to ensure the needs of the users (drivers), other road users (other drivers and Vulnerable Road Users (VRUs)), and the perspectives of stakeholders (driving instructors, insurance companies, authorities, certifiers, policy makers and regulators), as a key for obtaining viable and market-ready products. This main objective is further detailed in the following ones: 1) Multidisciplinary (human, social, economic, security, legal and ethical considerations) study of the requirements and expectations of the drivers, VRUs, and stakeholders to assure safety and adoption of automated vehicles. 2) Turning requirements into innovative interaction and monitoring concepts for driver-vehicle interaction in order to bridge the gap between users and automation technologies while assuring safe vehicles handling with reduced driver attention. 3) Turning requirements into innovative monitoring concepts for vehicle-environment interaction, enhancing current Advanced Driving Assistance Systems (ADAS) through the inclusion of predictive capabilities for better and faster ADAS reactions (nominal and emergency). 4) Validating requirements, user acceptance and impact assessment through realistic user-centric testing exercises under different scenario conditions. 5) Paving the way for the further adoption of the technology by the automation industry, by evolving on testing and pre-validation protocols, proposing advancements on the regulation and consumerist assessment.

AND-PD investigates causative mechanisms of anxiety (with or without depression) as a non-motor co-morbidity of Parkinson’s Disease (PD) and aims to understand the functional and pathological changes in the brainstem resulting from PD. This will provide new insights to advance personalised treatment of PD patients and open new research avenues supporting prevention, diagnosis and management of co-morbidities in PD patients. Using models of mental comorbidities of PD, AND-PD will investigate functional changes in brainstem nuclei and establish the link with the anxiety phenotype. Findings will be used to inform pre-clinical (rodent, non-human primate and biobank samples) and clinical research (fMRI and PET imaging, behavioural analysis, retrospective cohort analysis) to identify and correlate causalities between dysfunctional neurocircuitry and co-morbid anxiety of PD. To prove causality, AND-PD will i) analyse anxiety in neurotoxin and genetic models of PD; ii) assess the physiological impact and behavioural effects of interventions that selectively reproduce the damage caused by PD in the brainstem; and iii) determine the ability of RNA based approaches to counteract anxiety associated with PD. To demonstrate the link in human patients, AND-PD will analyse patient databases and correlate measures of anxiety with: 1) signs of neuropathology in PD brain samples’ brainstem and 2) clinical and functional biomarkers of dysfunctional neurotransmission through brainstem imaging in patients. AND-PD beneficiaries’ experience in translational research will help ‘bridge the gap’ between preclinical and clinical experiments and help identify new anatomical targets and markers (molecular, functional and pathological,) to support better diagnosis, management and treatment of co-morbidities in PD patients.