*Article* **The Potential Impact of Digital Biomarkers in Multiple Sclerosis in the Netherlands: An Early Health Technology Assessment of MS Sherpa**

**Sonja Cloosterman 1,\*, Inez Wijnands <sup>1</sup> , Simone Huygens <sup>2</sup> , Valérie Wester 2,3 , Ka-Hoo Lam <sup>4</sup> , Eva Strijbis <sup>4</sup> , Bram den Teuling <sup>1</sup> and Matthijs Versteegh <sup>2</sup>**


**Abstract:** (1) *Background*: Monitoring of Multiple Sclerosis (MS) with eHealth interventions or digital biomarkers provides added value to the current care path. Evidence in the literature is currently scarce. MS sherpa is an eHealth intervention with digital biomarkers, aimed at monitoring symptom progression and disease activity. To show the added value of digital biomarker–based eHealth interventions to the MS care path, an early Health Technology Assessment (eHTA) was performed, with MS sherpa as an example, to assess the potential impact on treatment switches. (2) *Methods:* The eHTA was performed according to the Dutch guidelines for health economic evaluations. A decision analytic MS model was used to estimate the costs and benefits of MS standard care with and without use of MS sherpa, expressed in incremental cost-effectiveness ratios (ICERs) from both societal and health care perspectives. The efficacy of MS sherpa on early detection of active disease and the initiation of a treatment switch were modeled for a range of assumed efficacy (5%, 10%, 15%, 20%). (3) *Results*: From a societal perspective, for the efficacy of 15% or 20%, MS sherpa became dominant, which means cost-saving compared to the standard of care. MS sherpa is cost-effective in the 5% and 10% scenarios (ICERs EUR 14,535 and EUR 4069, respectively). From the health care perspective, all scenarios were cost-effective. Sensitivity analysis showed that increasing the efficacy of MS sherpa in detecting active disease early leading to treatment switches be the most impactful factor in the MS model. (4) *Conclusions*: The results indicate the potential of eHealth interventions to be cost-effective or even cost-saving in the MS care path. As such, digital biomarker–based eHealth interventions, like MS sherpa, are promising cost-effective solutions in optimizing MS disease management for people with MS, by detecting active disease early and helping neurologists in decisions on treatment switch.

**Keywords:** digital biomarkers; eHealth; digital health; AI; (early) Health Technology Assessment; multiple sclerosis; home monitoring; MS disease activity; MS disease progression; early detection; disease modelling; digital therapeutics
