Next Article in Journal
Persistence of the Effects of the COVID-19 Lockdown on Sleep: A Longitudinal Study
Next Article in Special Issue
Health Economic Impact of Software-Assisted Brain MRI on Therapeutic Decision-Making and Outcomes of Relapsing-Remitting Multiple Sclerosis Patients—A Microsimulation Study
Previous Article in Journal
Writing Units or Decades First in Two Digit Numbers Dictation Tasks: The Case of Arabic—An Inverted Language
Previous Article in Special Issue
Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data
Review

Digital Biomarkers in Multiple Sclerosis

Multiple Sclerosis Center Dresden, Center of Clinical Neuroscience, Department of Neurology, University Clinic Carl-Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, 01307 Dresden, Germany
*
Author to whom correspondence should be addressed.
These Authors have contributed equally to this work.
Academic Editor: Emilio Portaccio
Brain Sci. 2021, 11(11), 1519; https://doi.org/10.3390/brainsci11111519
Received: 20 October 2021 / Revised: 10 November 2021 / Accepted: 11 November 2021 / Published: 16 November 2021
(This article belongs to the Special Issue Digital Innovation in Multiple Sclerosis Management)
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. View Full-Text
Keywords: multiple sclerosis; digital biomarkers; digital health technology; eHealth; precision medicine; personalized therapy; big data; digital twin multiple sclerosis; digital biomarkers; digital health technology; eHealth; precision medicine; personalized therapy; big data; digital twin
Show Figures

Figure 1

MDPI and ACS Style

Dillenseger, A.; Weidemann, M.L.; Trentzsch, K.; Inojosa, H.; Haase, R.; Schriefer, D.; Voigt, I.; Scholz, M.; Akgün, K.; Ziemssen, T. Digital Biomarkers in Multiple Sclerosis. Brain Sci. 2021, 11, 1519. https://doi.org/10.3390/brainsci11111519

AMA Style

Dillenseger A, Weidemann ML, Trentzsch K, Inojosa H, Haase R, Schriefer D, Voigt I, Scholz M, Akgün K, Ziemssen T. Digital Biomarkers in Multiple Sclerosis. Brain Sciences. 2021; 11(11):1519. https://doi.org/10.3390/brainsci11111519

Chicago/Turabian Style

Dillenseger, Anja, Marie L. Weidemann, Katrin Trentzsch, Hernan Inojosa, Rocco Haase, Dirk Schriefer, Isabel Voigt, Maria Scholz, Katja Akgün, and Tjalf Ziemssen. 2021. "Digital Biomarkers in Multiple Sclerosis" Brain Sciences 11, no. 11: 1519. https://doi.org/10.3390/brainsci11111519

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop