About clinical studies
iPROLEPSIS will perform four different clinical studies:
PsA digital phenotyping and inflammation drivers study.
Mast cells and optoacoustics-enabled joint and microvascular imaging study.
Inflammation digital biomarkers validation study.
Prevention of PsA inflammation through digital care: an intervention study.
Clinical studies will be conducted in 5 countries:
Definition of novel optoacoustic biomarkers of psoriasis and psoriatic arthritis (iPROLEPSIS-MOJMI)Mast cells and optoacoustics-enabled joint and microvascular imaging (iPROLEPSIS-MOJMI) study. The proposed multiscale (mesoscopic with RSOM and macroscopic with MSOT) approach aims at exploring and defining novel image-based biomarkers in order to describe the pathophysiological changes characterizing the disease and predict the transition from PsO to PsA. In other words, the unique multiscale nature of optoacoustics is expected to render skin microvasculature a window to later systemic (joint) effects of psoriasis and, thus, improve the prognosis in future patients with PsO. OBJECTIVES Primary objectives To define novel inflammatory mast cell, MSOT- and RSOM extracted biomarkers in patients with PsO/PsA. To quantify the changes of the novel inflammatory mast cell, MSOT- and RSOM-extracted biomarkers' with increasing disease severity. Secondary objectives To reveal correlations among the mast cells and the MSOT-and RSOM-extracted inflammatory biomarkers in patients with PsO/PsA. To define a novel index derived from mast cells, MSOT- and RSOM-based features to enable the early detection of PsA in patients with PsO or high risk for developing PsO.
Prevention of PsA inflammation through digital care: an intervention study (iPROLEPSIS-PPIDC)This study blends the findings of the newly developed digital biomarkers, the early findings of the triggers: stress, mechanical stress and changes in microbiome from PsA digital phenotyping and inflammation drivers study (iPROLEPSIS-PDPID), to provide a personalised approach to deal with the triggers with state-of-the-art interventions. OBJECTIVES Primary objectives In PsA patients with low disease activity a personalised intervention on food, physical activity and stress based on a personal profile of stress, mechanical stress and microbiome will be compared to usual care on inflammation development as detected by the newly developed digital biomarker system and clinical examination. Secondary objectives to evaluate take up and acceptability of the digital biomarker and intervention as part of normal medical treatment among patients, doctors and nurses; to assess compliance with the personalised intervention.
PsA digital phenotyping and inflammation drivers study (iPROLEPSIS-PDPID)Development cohort of smartphone and smartwatch-based, AI-driven digital biomarkers for remote assessment and monitoring of people with psoriatic arthritis. Measure To develop novel smartphone- and smart device (belt, ring, camera) digital biomarkers for the assessment of inflammatory symptoms with special focus on the recognition of changes in movement patterns, pain, fatigue, morning stiffness in comparison to the gold standard – medical evaluation by clinical evaluation of the joints, tendons and skin. Predict To predict the change from uninflamed to inflamed using three triggers that may cause longstanding inflammation in psoriatic arthritis patients at risk for flare. Those three triggers are stress, mechanical stress and changes in the gut microbiome. OBJECTIVES Primary objectives to provide accurate, factual and clinically relevant records of the self-contained smartphone and smartwatch based, AI-driven digital biomarker system in the detection of PsA specific inflammation; to predict accurate, factual and clinically relevant PsA specific inflammation. Secondary objectives to determine interperson reliability of the AI-driven digital biomarker system; to determine construct validity against clinical assessment of inflammation; to determine construct validity against patient assessment of inflammation; to determine clinically relevant changes in the AI-driven digital biomarker system; to determine minimal detectable difference in the AI-driven digital biomarker system; to assess the interperson variation of stress, mechanical stress and changes in gut microbiome on the occurrence of inflammation; to evaluate the compliance and satisfaction of the users with the smartphone and smartwatch-based, AI driven digital monitoring system. The study is designed to develop a new way of measuring inflammation in patient with psoriatic arthritis.
Inflammation digital biomarkers validation study (iPROLEPSIS-IDBV)Finding people that will convert from healthy to inflamed is a difficult task in Immune Mediated Inflammatory Disease (IMID). Initial symptoms look just like any other musculoskeletal disorder such as back pain, finger pain or achilles tendon problems. Over time symptoms can go either temporarily away, become chronic or become so severe that doctor care is needed. Early identification of people with IMID would greatly benefit their quality of live, keeps them at work and prevents high health care cost due to expensive medication. Digital biomarkers will give us for the first time the ability to study the conversion from musculoskeletal disorder to immune mediated inflammatory joint and tendon disease. The aim of this study to validate our digital biomarkers findings in PsA in psoriasis patients. OBJECTIVES Primary objectives to validate accurate, factual and clinically relevant records of the self-contained smartphone and smartwatch-based, AI-driven digital biomarker system in the detection of IMID specific joint or tendon inflammation. Secondary objectives to evaluate take up and acceptability of the digital biomarker in the wild; to evaluate the impact of missing data in detecting inflammation; to assess the number of false positives when data is captured in the wild; to assess the interperson variation of stress and mechanical stress. The aim is to identify inflammation with a software based medical device. This software will consist of an algorithm analysing data collected in the wild via smart devices: phone, watch, ring.