Digital Twins in Clinical Neurology: From Concept to Clinical Application in Multiple Sclerosis
Year: 2026
Type: review
Abstract: INTRODUCTION: Patient digital twins (DT) are emerging as a promising paradigm for personalised and predictive healthcare. In neurology, and particularly in multiple sclerosis (MS), the availability of longitudinal, multimodal data provides a strong foundation for developing patient-specific digital models, including simulation-based and mechanistic approaches. However, it remains unclear to what extent current approaches represent integrated, clinically embedded DT systems. METHODS: We conducted a narrative review to synthesise current concepts, modelling approaches and translational challenges of DT in neurology, using MS as an illustrative use case. Existing approaches were mapped to core DT components, including data integration, predictive modelling, dynamic updating and clinical integration. RESULTS: Current DT-related approaches in MS demonstrate substantial progress across complementary development tracks, including multimodal data integration, predictive modelling, digital biomarkers, mechanistic simulations, virtual-patient frameworks and in silico trials. These capabilities represent important building blocks of DT development but have not yet been fully integrated into continuously operating clinical systems. Core DT functionalities, including continuous bidirectional data exchange, real-time model updating and closed-loop interaction with clinical workflows, remain limited. Key challenges include data fragmentation, limited interoperability, lack of standardised validation, and regulatory, ethical and economic constraints. CONCLUSION: MS represents a highly suitable model domain for DT development. Future progress will depend on further maturing and validating individual modelling and data-integration capabilities, as well as on their integration into continuously updating, clinically embedded systems. Robust validation, scalable infrastructures and appropriate governance frameworks will be essential to establish safe, effective and clinically actionable use in practice.
Source: European Journal of Neurology
DOI: 10.1111/ene.70791
Institutions: University Hospital Carl Gustav Carus, Centre for Tactile Internet with Human-in-the-Loop, Technische Universität Dresden, Universitätsklinikum des Saarlandes, Saarland University, Universitätsmedizin Greifswald, Düsseldorf University Hospital, University Hospital Münster, Else Kröner Fresenius Center for Digital Health
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,600
Funders: Eli Lilly and Company, AstraZeneca, Sanofi, Biogen, Teva Pharmaceutical Industries, Alexion Pharmaceuticals, Celgene, Hexal AG, B. Braun-Stiftung, Amicus Therapeutics, Fresenius Medical Care North America, Mylan, Argenx, Multiple Sclerosis Society, European Commission, Deutscher Akademischer Austauschdienst, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Technische Universität Dresden, Daimler und Benz Stiftung, Heinrich-Heine-Universität Düsseldorf, Novo Nordisk, Deutschen Multiple Sklerose Gesellschaft, Deutsche Alzheimer Gesellschaft, Ipsen, Neuraxpharm, Gemeinsame Bundesausschuss, MedDay Pharmaceuticals, Directorate-General for Research and Innovation, Chugai Pharmaceutical, Bayer Vital, Novo Nordisk Pharma, Bundesinstitut für Risikobewertung, Cilag
OpenAlex ID: W7224111337