A future of AI-driven personalized care for people with multiple sclerosis

Research output: Contribution to journalReview articleContributedpeer-review

Contributors

  • Jelle Praet - , icometrix NV, Leuven, Belgium. (Author)
  • Lina Anderhalten - , Experimental and Clinical Research Center (ECRC) (Author)
  • Giancarlo Comi - , Vita-Salute San Raffaele University (Author)
  • Dana Horakova - , General University Hospital in Prague (Author)
  • Tjalf Ziemssen - , Department of Neurology (Author)
  • Patrick Vermersch - , Université de Lille (Author)
  • Carsten Lukas - , Catholic Hospital Bochum gGmbH (Author)
  • Koen van Leemput - , Aalto University (Author)
  • Marjan Steppe - , European Charcot Foundation, Brussels, Belgium. (Author)
  • Cristina Aguilera - , SYNAPSE Research Management Partners, Madrid, Spain. (Author)
  • Ella Maria Kadas - , Nocturne GmbH, Berlin, Germany. (Author)
  • Alexis Bertrand - , AB Science (Author)
  • Jean van Rampelbergh - , Imcyse SA, Liège, Belgium. (Author)
  • Erik de Boer - , Bristol-Myers Squibb (Author)
  • Vera Zingler - , F. Hoffmann-La Roche AG (Author)
  • Dirk Smeets - , icometrix NV, Leuven, Belgium. (Author)
  • Annemie Ribbens - , icometrix NV, Leuven, Belgium. (Author)
  • Friedemann Paul - , Charité – Universitätsmedizin Berlin (Author)

Abstract

Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system resulting in progressive disability accumulation. As there is no cure available yet for MS, the primary therapeutic objective is to reduce relapses and to slow down disability progression as early as possible during the disease to maintain and/or improve health-related quality of life. However, optimizing treatment for people with MS (pwMS) is complex and challenging due to the many factors involved and in particular, the high degree of clinical and sub-clinical heterogeneity in disease progression among pwMS. In this paper, we discuss these many different challenges complicating treatment optimization for pwMS as well as how a shift towards a more pro-active, data-driven and personalized medicine approach could potentially improve patient outcomes for pwMS. We describe how the 'Clinical Impact through AI-assisted MS Care' (CLAIMS) project serves as a recent example of how to realize such a shift towards personalized treatment optimization for pwMS through the development of a platform that offers a holistic view of all relevant patient data and biomarkers, and then using this data to enable AI-supported prognostic modelling.

Details

Original languageEnglish
Article number1446748
JournalFrontiers in immunology
Volume15
Publication statusPublished - 2024
Peer-reviewedYes

External IDs

PubMedCentral PMC11366570
Scopus 85203000845

Keywords

Keywords

  • Artificial Intelligence, Biomarkers, Disease Progression, Humans, Multiple Sclerosis/therapy, Precision Medicine/methods, Prognosis, Quality of Life