PUC1: MES-CoBraD Multidisciplinary Multisource Real-World Data Assessment Protocol

PUC1 presents a novel clinical protocol for multisource multidisciplinary RWD acquisition and integration within and between CoBraD from multiple institutions. This protocol addresses challenges of CoBraD underdiagnosis, misdiagnosis, suboptimal diagnosis, and delay in diagnosis of primary and comorbid CoBraD, by considering the complex multidimensional CoBraD pathophysiology and exploiting the combined expertise of leading researchers in their respective field from across Europe. This novel clinical assessment protocol based on RWD serves in improving clinical outcomes and quality of life for patients with CoBraD, and become the prototypical example for the assessment and management of other chronic complex conditions. The database developed can be leveraged after the Project’s completion and will be made available to other researchers in pursuing novel scientific objectives and in keeping with Open Science and FAIR principles.

Graphic representation of PUC1

MES-CoBraD Multidisciplinary Multisource RWD Assessment Protocol. RWD are acquired from multiple sources and reflective of multiple disciplines of all CoBraD in a temporally structured flow within a week, to maximize their impact in deep-phenotyping of CoBraD. Sleep-mediated evaluations, such as cognitive and blood testing, are significant on their own, but also of their temporal variability throughout the circadian rhythm. Questionnaire data are obtained in clinic or out-of-clinic by patients, caregivers, and clinicians. Imaging, medical device, and consumer technology data, are recorded as acquired in real-world settings throughout the project’s duration, accounting for timing of their acquisition to other modules. Note: NPT: Neuropsychological Testing; MRI: Magnetic Resonance Imaging; PAP: Positive Airway Pressure; NIV: Non-Invasive Ventilation

PUC2: MES-CoBraD Advanced Analytics Deep-Phenotyping and Prognostication

PUC2 expands on the use of advanced analytics modules of supervised data analyses (i.e., computationally intensive data modelling to discover useful information) and artificial intelligence (i.e., algorithms of data processing that allow learning and problem-solving) towards deep-phenotyping of CoBraD and their interrelationships, and predicting longitudinal health-related outcomes on individual patients. This allows use of precision medicine tools towards personalized decision making. PUC2 follows the principle that assessment and management of chronic complex conditions are improved through comprehensive multidisciplinary analyses of big interrelated data represented into clinically and socially relevant evidence-based outcomes. PUC2 leverages the computational power of complex multidimensional information processing of advanced analytics with the goal of developing the tools for researchers and, eventually, clinicians to use in assessment and management of CoBraD.

PUC3: MES-CoBraD Real-World Therapy Repurposing and Approved Indication Reassessment

PUC3 assesses cross-sectionally and longitudinally clinical outcomes in relation to established therapies in real-world practice. Pursuing comparative effectiveness research and real-world clinical trials on existing healthcare interventions can help improve population-level impact and personalized medicine patient-centered outcomes. These models of post-approval therapy evaluation via PUC3 will inform stakeholders in making informed decisions to improve healthcare at both the individual and population levels. The MES-CoBraD Platform is developed with the potential to be usable for such real-world studies.  PUC3 leverages the prospectively and retrospectively acquired multisource multidisciplinary RWD integrated on the MES-CoBraD Platform and the Platform’s advanced analytic tools to address therapeutic clinical and research challenges, including suboptimal or contraindicated therapies, need for effective treatments, assessment of psychosocial impact of therapies, patient access to healthcare and compliance, monitoring of approved therapies in real-world practice, and multiple failed costly clinical trials, through research protocols combining scientific expertise and resources.

PUC4: Development and Validation of a multidisciplinary expert system for the assessment and management of complex brain disorders – MES-CoBraD

Graphic representation of PUC4 MES-CoBraD algorithmThe end product of MES-CoBraD development is a recursive decision algorithm that will help the user reach a precise diagnosis of CoBraD by exploiting modules tested in PUC1 and PUC2, and, in parallel, optimize therapies by applying modules tested in PUC3.


MES-CoBraD algorithm. The Expert System end-product (a) is given a task at the start of the algorithm, (b) it then identifies a starting point in acquiring the next relevant RWD, either directly through MES-CoBraD questionnaire RWD modules and integrated external packages or through end-user uploadable RWD, (c) that is next evaluated based on expert and advanced analytics modules to provide an interim result, which can be actionable by the user. (d) If the analytics result does not satisfy predefined end-of-process criteria for the specific task, the process is recursively repeated, else it ends.


Graphic representation of PUC4 model development and validation algorithmSeparate-sample Plan of Exploratory Data Analysis followed by Confirmatory Data Analysis for Multidisciplinary Expert System Model Development. One of more prototype models of MES developed based on 80% of training RWD during the two years of the study will be validated on 20% of the remaining test RWD.