Subtle impairments in accomplishing daily activities are sometimes reported among the first signs of a disorder that will progressively develop towards more severe disabilities for individuals affected with NDD and IMID. Identifying the ADLs that first or more consistently are affected by the disorders and tracing their progression using original digital solution is a key aspect of the present project. In fact, advances in micro-sensors and mobile technologies have the potential to enable seamless, continuous, objective measurements of symptoms and disabilities, providing more precise and higher frequency data collection. The early identification of impairment and the possibility to follow its worsening with precision and reliability are essential tools for assessing the effects of novel treatments that should target the disorder in its early phases. In fact, if the disorders progress beyond a certain point, the disabilities may not be reversible, justifying early interventions.
Neurodegenerative movement disorders (NMD) and immune mediated inflammatory diseases (IMID) can cause considerable disability and morbidity in spite of the availability of approved treatments. Recent estimates suggest that neurodegenerative disorders are becoming one of the fastest growing costs for healthcare systems. Movement disorders, in particular Parkinson's disease (PD), affect about 1.2 million European citizens, a number set to double by 2050 While rarer, the burden of Huntington's disease can be up to 5 times higher than that of PD patients.
Digital technology, in particular remote monitoring systems, if properly implemented and validated, could provide a critical help in improving measurements of efficacy by increasing sensitivity and precision, reducing variability, and enhancing their ecological validity making them closer to the actual unmet needs of patients. This project will develop a technology platform to collect and analyse sensor/generated datasets, principally high resolution passively and actively collected digital measurements, i.e. actigraphy, socialisation parameters and momentary self-reported assessments, mainly using (but not limited to) wearables and smartphone sensors and apps.
Digital transformation of clinical and real-world measures of ADL / quality of life measures relevant to patients and care-givers will give deeper and more detailed insights into how diseases progress and cause disabilities in patients, which, in turn, will enable development of interventions that better address these clinical deficits and disabilities.
Digital endpoints when combined with patient self-reported outcomes and other traditional clinical measures will provide a more valid and complete assessment of patient and care-giver impact of disease and their treatments.
Digital transformation of clinical and real-world endpoints will enable larger and more inclusive clinical trials and reduce patient burden thus allowing assessment of interventions in more diverse and representative populations.
Use of passive digital technologies will increase the efficiency of clinical trials, enabling faster clinical development and a reduction in the time taken to bring new therapies to patients. These technology enabled endpoints with passive data collection will make larger and longer follow-on studies to assess real world impact of therapies on patients possible, thus enabling more effective value driven health care decision making.
It is expected that, in the long run, this project will enable the development and evaluation of more effective therapies for patients thus improving outcomes for patients and reducing cost for all stakeholders.
Applicants should also demonstrate how they will impact on the competitiveness and industrial leadership of Europe by, for example, engaging suitable SMEs.