The application scenarios for MES-CoBraD focus on the adoption of innovative information and communication technologies by healthcare stakeholders as well as by the users. The MES-CoBraD Platform will address several of the clinical, research and technological challenges.
The application scenarios will pursue to advance scientific knowledge in CoBraD, serve as examples of the exploitation potential of the MES-CoBraD Platform, maximising novelty and impact, and highlighting the platform’s integration potential of multisource RWD for diverse clinical-research projects in CCC through its abstract methodology. Each scenario will address clinical, research, and technological challenges faced in medicine, and especially in CoBraD, and each scenario is an indicative case of the MES-CoBraD project’s Expected Impact.
MES-CoBraD Multidisciplinary Multisource Real-World Data Assessment Protocol
The first use case is a representative case of how the MES-CoBraD Platform will address several of the clinical, research and technological challenges that exist. Specifically, this case 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 will serve in improving clinical outcomes and quality of life for patients with CoBraD and becomes the prototypical example for the assessment and management of other CCC. The prospective database developed can be leveraged after the Project’s completion by the Consortium and will be made available to other researchers in pursuing novel scientific objectives and in keeping with Open Science principles.
The current state-of-the-art in evaluating people with CoBraD is for clinicians and their teams to address a patient’s specific complaint or syndromic presentation in isolation, not addressing other comorbidities or the multidisciplinary complexity of a syndrome. The lack of comprehensive assessments is one of the most important factors explaining delays in diagnosis as many patients are not aware and clinicians may overlook that a certain symptom is significant to mention in clinical practice or are simply unaware of concerning signs. And, although comprehensive assessments may intuitively seem labor-intensive and costly, with the scientific advancements of recent years and optimized procedures of acquiring RWD, the effort may only be at the front end of training a system in making its practices more effective and efficient, allowing for cost-effectiveness and better-quality care down the road.
Hence, MES-CoBraD solution aims to address several of the clinical, research and technological challenges. Specifically, MES-CoBraD solution 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 will serve in improving clinical outcomes and quality of life for patients with CoBraD, and become the prototypical example for the assessment and management of other CCC. The prospective database developed can be leveraged after the Project’s completion by the Consortium and will be made available to other researchers in pursuing novel scientific objectives and in keeping with Open Science principles.
MES-CoBraD Advanced Analytics Deep-Phenotyping and Prognostication
This use case highlights the potential of MES-CoBraD Platform in advancing precision medicine through advanced analytics modules. The current situation is that a single clinician or even a multidisciplinary referral center, have limited expertise in assessing fully multidisciplinary multisource RWD, and this is further limited by the increasing size of multidimensional data that we are becoming aware are relevant in improving decision making.
The MES-CoBraD Platform will leverage 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, and CCC in general. Since, this MES-CoBraD’s solution will help with improving underdiagnosis, misdiagnosis, suboptimal diagnosis, and delay in diagnosis of primary and comorbid CoBraD, integrating and analyzing complex multidimensional CoBraD pathophysiology through collaborative research efforts from across Europe.
MES-CoBraD Real-World Therapy Repurposing and Approved Indication Reassessment
This use case will test the MES-CoBraD Platform in cross-sectionally and longitudinally assessing clinical outcomes in relation to established therapies in real-world practice. Current studies indicate a growing concern that clinical trial results do not have the expected impact in real-world practice. Instead, 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. Although, Real-world clinical practice therapies of CoBraD often have variable effects across patients, whether they are pharmacological or not. For example, some people with epilepsy may respond to an anti-epileptic drug but others will not. The response to cholinesterase inhibitors is also variable between people with Alzheimer’s disease. Even the tolerance and effectiveness of PAP/NIV therapy in sleep apnea varies between people. There are several clinical (e.g., genetic, pharmacokinetic, pharmacodynamic, within syndrome variability) and social (e.g., varied marketable product quality, access to regular treatment) reasons for such discrepancies. Improving precision medicine practices to deep-phenotype patients and personalizing assessments is a methodology gaining traction the past years in improving outcomes.
Hence, this solution will leverage 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. The MES-CoBraD Platform aims at performing cross-sectional and longitudinal analyses looking at approved therapeutic interventions and examine their correlation with CoBraD symptom severity and disease progression.
Development and Validation of a multidisciplinary expert system for the assessment and management of complex brain disorders – MES-CoBraD
In this use case the focus is on the development of the MES-CoBraD and its cross-validation throughout the project’s life. Currently, with the breadth and depth of knowledge in CoBraD it is impossible for a single clinician or multidisciplinary team of clinicians to have up-to-date expert knowledge of CoBraD and their interrelations, and, even more, make complex multidisciplinary decisions in pursuing specific diagnostic assessments and recommending the best evidence-based therapies. MES-CoBraD goal is the eventually integrating the platform in clinical practice aims to provide an invaluable tool to clinicians and improve qualitative and quantitative clinical and social outcomes in patients with CoBraD, making the MES-CoBraD the prototypical example for the assessment and management of other CCC as well. Currently, there is no single Platform containing an Expert System that integrates multisource multidimensional RWD across CoBraD or, even more, that incorporates advanced analytics modules for clinical and social outcome assessment and management. Expert systems with decision trees have been developed in Sleep Medicine (SleepEval®), obtaining predominantly subjective questionnaire data only and targeting specific sleep disorders rather than sleep disorders in their entirety. In dementia, expert systems are restricted to pattern recognition algorithms of imaging RWD and do not reflect decision trees. Similarly, in epilepsy, reported expert systems are classification algorithms, usually of classifying EEG epileptiform activity, rather than decision tree algorithms, and may only have internal and not external cross-validation with risk of overfitting.
Hence, the MES-CoBraD platform will focus on the development of the Multidisciplinary Expert System for the Assessment and Management of CoBraD and its cross-validation. The MES-CoBraD platform aims at being an Expert System in medical science is a decision-making algorithm to achieve a medically relevant goal (diagnostic or therapeutic), mimicking or, ideally, surpassing a human expert. The MES-CoBraD platform relies on a database that is usually large, and advanced analytics modelled according to the available data and/or an expert’s supervised decision-algorithms. Ideally, it has the flexibility to update its database and its analytics modules in order to constantly improve its deliverables. The MES-CoBraD firstly, aims at addressing the clinical, research, and technological challenges in CoBraD. Also, MES-CoBraD goal is to eventually intergrate the MES-CoBraD platform in clinical practice aims to provide an invaluable tool to clinicians and improve qualitative and quantitative clinical and social outcomes in patients with CoBraD, making the MES-CoBraD the prototypical example for the assessment and management of other CCC as well.