An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient’s characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively advance the necessary implementation of an individualized innovative management of MS. Through artificial intelligence-based analysis of several disease parameters – including clinical and para-clinical outcomes, multi-omics, biomarkers, patient-related data, information about the patient’s life circumstances and plans, and medical procedures – a digital twin paired to the patient’s characteristic can be created, enabling healthcare professionals to handle large amounts of patient data. This can contribute to a more personalized and effective care by integrating data from multiple sources in a standardized manner, implementing individualized clinical pathways, supporting physician-patient communication and facilitating a shared decision-making. With a clear display of pre-analyzed patient data on a dashboard, patient participation and individualized clinical decisions as well as the prediction of disease progression and treatment simulation could become possible. In this review, we focus on the advantages, challenges and practical aspects of digital twins in the management of MS. We discuss the use of digital twins for MS as a revolutionary tool to improve diagnosis, monitoring and therapy refining patients’ well-being, saving economic costs, and enabling prevention of disease progression. Digital twins will help make precision medicine and patient-centered care a reality in everyday life.

The low agreement on health and treatment priorities between patients and physicians necessitates better communication between the two parties to strengthen mutual understanding.

For incurable diseases, such as multiple sclerosis (MS), the prevention of progression and the preservation of quality of life play a crucial role over the entire therapy period. In MS, patients tend to become ill at a younger age and are so variable in terms of their disease course that there is no standard therapy. Therefore, it is necessary to enable a therapy that is as personalized as possible and to respond promptly to any changes, whether with noticeable symptoms or symptomless. Here, measurable parameters of biological processes can be used, which provide good information with regard to prognostic and diagnostic aspects, disease activity and response to therapy, so-called biomarkers Increasing digitalization and the availability of easy-to-use devices and technology also enable healthcare professionals to use a new class of digital biomarkers—digital health technologies—to explain, influence and/or predict health-related outcomes. The technology and devices from which these digital biomarkers stem are quite broad, and range from wearables that collect patients’ activity during digitalized functional tests (e.g., the Multiple Sclerosis Performance Test, dual-tasking performance and speech) to digitalized diagnostic procedures (e.g., optical coherence tomography) and software-supported magnetic resonance imaging evaluation. These technologies offer a timesaving way to collect valuable data on a regular basis over a long period of time, not only once or twice a year during patients’ routine visit at the clinic. Therefore, they lead to real-life data acquisition, closer patient monitoring and thus a patient dataset useful for precision medicine. Despite the great benefit of such increasing digitalization, for now, the path to implementing digital biomarkers is widely unknown or inconsistent. Challenges around validation, infrastructure, evidence generation, consistent data collection and analysis still persist. In this narrative review, we explore existing and future opportunities to capture clinical digital biomarkers in the care of people with MS, which may lead to a digital twin of the patient. To do this, we searched published papers for existing opportunities to capture clinical digital biomarkers for different functional systems in the context of MS, and also gathered perspectives on digital biomarkers under development or already existing as a research approach.

(1) Background: eHealth interventions play a growing role in shaping the future healthcare system. The integration of eHealth interventions can enhance the efficiency and quality of patient management and optimize the course of treatment for chronically ill patients. In this integrative review, we discuss different types of interventions, standards and advantages of quality eHealth approaches especially for people with multiple sclerosis (pwMS). (2) Methods: The electronic databases PubMed, Cochrane and Web of Science were searched to identify potential articles for eHealth interventions in pwMS; based on 62 articles, we consider different ways of implementing health information technology with various designs. (3) Results: There already exist some eHealth interventions for single users with a single-use case, interventions with a social setting, as well as eHealth interventions that integrate various single and social interventions and even those that may be used additionally for complex use cases. A key determinant of consumer acceptance is a high-quality user-centric design for healthcare practitioners and pwMS. In pwMS, the different neurological disabilities should be considered, and particular attention must be paid to the course of the treatment and the safety processes of each treatment option. (4) Conclusion: Depending on the field of application and the respective users, interventions are designed for single, social, integrated or complex use. In order to be accepted by their target group, interventions must be beneficial and easy to use.

Background: Multiple Sclerosis is a chronic inflammatory disease of the central nervous system that requires a complex, differential, and lifelong treatment strategy, which involves high monitoring efforts and the accumulation of numerous medical data. A fast and broad availability of care, as well as patient-relevant data and a stronger integration of patients and participating care providers into the complex treatment process is desirable. The aim of the ERDF-funded project "Integrated Care Portal Multiple Sclerosis" (IBMS) was to develop a pathway-based care model and a corresponding patient portal for MS patients and health care professionals (HCPs) as a digital tool to deliver the care model. Methods: The patient portal was created according to a patient-centered design approach which involves both the patients' and the professionals' view. Buurmann's five iterative phases were integrated into a design science research process. A problem analysis focusing on functions and user interfaces was conducted through surveys and workshops with MS patients and HCPs. Based on this, the patient portal was refined and a prototype of the portal was implemented using an agile software development strategy. Results: HCPs and patients already use digital hardware and are open to new technologies. Nevertheless, they desire improved (digital) communication and coordination between care providers. Both groups require a number of functions for the patient portal, which were implemented in the prototype. Usability tests with patients and HCPs are planned to consider whether the portal is deemed as usable, acceptable as well as functional to prepare for any needed ameliorations. Discussion: After testing the patient portal for usability, acceptability, and functionality, it will most likely be a useful and high-quality electronic health (eHealth) tool for patient management from day care to telerehabilitation. It implements clinical pathways in a manner which is comprehensible for patients. Future developments of the patient portal modules could include additional diseases, the integration of quality management and privacy management tools, and the use of artificial intelligence to personalize treatment strategies.