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Speech-based digital endpoints track ALS progression and align with standard clinical outcomes: evidence from the VRG50635 trial

  • Michael Neumann*
  • , Hardik Kothare
  • , Meredith Bartlett
  • , Oliver Roesler
  • , Christiane Suendermann-Oeft
  • , Abhishek Hosamath
  • , Lakshmi Arbatti
  • , David Pautler
  • , David Suendermann-Oeft
  • , Diego Cadavid
  • , Robert H. Scannevin
  • , Ines Hoffmann
  • , Anil Tarachandani
  • , Tara Haley
  • , Shane Raines
  • , Philip Van Damme
  • , Pentti Tienari
  • , Eino Solje
  • , Manu Jokela
  • , Angela Genge
  • Colleen O’Connell, Ruben P.A.van Eijk, Leonard H.van den Berg, Vikram Ramanarayanan*
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

We report on the utility of speech-based digital endpoints measured during a Phase 1b study of VRG50635 in Amyotrophic Lateral Sclerosis (ALS). Fifty-four participants with ALS were enrolled and participated in an 8-week pretreatment run-in, followed by three 8-week dosing periods and an 8-week follow-up. They completed a speech assessment every two weeks in the clinic or at home. We observed moderate to high correlations between digital measures of speech timing and articulatory motor function, and the ALS Functional Rating Scale-Revised, slow vital capacity and plasma neurofilament light chain. Furthermore, speech measures can show functional decline before the ALSFRS-R does, while also capturing differences between participants with bulbar symptoms and those without. The results support the feasibility and utility of digital speech endpoints to study disease impact in ALS clinical trials.

Original languageEnglish
Article number20088
JournalScientific Reports
Volume16
Issue number1
DOIs
Publication statusPublished - 2026

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