Clinical Protocol for the IDEA-FAST Study: Assessing Digital Metrics of Fatigue, Sleep Quality, and Daytime Sleepiness in a Cohort of 2000 Participants - Report - MDSpire

Clinical Protocol for the IDEA-FAST Study: Assessing Digital Metrics of Fatigue, Sleep Quality, and Daytime Sleepiness in a Cohort of 2000 Participants

  • By

  • Walter Maetzler

  • Stefan Avey

  • Andrea Pilotto

  • C Janneke van der Woude

  • Christopher A Lamb

  • Ralf Reilmann

  • Teemu Ahmaniemi

  • Nadir Ammour

  • Svenja Aufenberg

  • Luisa Avedano

  • Neil Basu

  • Simon Beniston

  • Sofia Bonomelli

  • Susanne T de Bot

  • Diogo Branco

  • Ian Bruce

  • Christopher Neil Bull

  • Neshat Chareh

  • Meenakshi Chatterjee

  • Hector Chinoy

  • Jade Chisholm

  • Hayley Connolly

  • Francesca Cormack

  • Leonor Correia Guedes

  • Cliona Cowhig

  • Dina De Sousa

  • Silvia Del Din

  • Monique Devillers

  • Inês M Dias

  • Colin Bone Dodds

  • Mary Doona

  • Annika Dvinskis

  • Joaquim J Ferreira

  • Konstantinos Fourlakis

  • Ulli Funken

  • Kay Goulden

  • Johanna Graeber

  • Miriam Grande Gordon

  • Hanna Graßhoff

  • Tiago Guerreiro

  • Tina Hagen-Hurley

  • Clint Hansen

  • Sinead Harney

  • Ailsa Hart

  • Chloe Hinchliffe

  • Sophia Hinz

  • Marthe Alver Hovsbakken

  • Michael Jackson

  • Lauren John

  • Hanna Kaduszkiewicz

  • Jérôme Kalifa

  • Niamh Kelly

  • Nick Kennedy

  • Norelee Kennedy

  • Juha M Kortelainen

  • Laura C. M. Kuijper

  • Samuel Labrecque

  • Yasmin Laidler

  • Tanja Lange

  • Maria Boge Lauvsnes

  • Jimmy K. Limdi

  • Ellen Lirani-Silva

  • Victoria Macrae

  • Corina Maetzler

  • Mayca Marín

  • Dario Masullo

  • Tania Nightingale

  • Alessandro Padovani

  • Miles Parkes

  • Emma Paulides

  • Clémence Pinaud

  • Zaireen Pios

  • Costantino Pitzalis

  • Alexandra Prodan

  • Rana Zia Ur Rehman

  • Gabriela Riemekasten

  • Andrea Rizzardi

  • Matthew W Roche

  • Lynn Rochester

  • Robbin Romijnders

  • Stefan Schreiber

  • Katarina Schwarzová

  • Christian Selinger

  • Klaus Seppi

  • Louise Stockley

  • Sreedhar Subramanian

  • Kai Sun

  • Nick Taptiklis

  • Gerlynn Tiongson

  • Kasper F van der Zwaan

  • Evert-Ben van Veen

  • Louise Warren

  • David Wenn

  • Grzegorz Witkowski

  • Alison Yarnall

  • Frederic Baribaud

  • Geert Van Gassen

  • Nikolay V. Manyakov

  • Wan-Fai Ng

  • IDEA-FAST Project Consortium

  • March 1, 2026

  • 0 min

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Clinical Protocol for IDEA-FAST: Digital Metrics of Fatigue and Sleep in 2000 Participants

Overview

The IDEA-FAST study is a large, multinational observational study designed to identify objective digital endpoints for fatigue, impaired sleep quality, and daytime sleepiness across six chronic diseases and healthy volunteers. It involves 2000 participants monitored using digital health technologies over multiple visits to capture continuous symptom fluctuations.

Background

Fatigue, poor sleep quality, and daytime sleepiness are common and debilitating symptoms in neurodegenerative and immune-mediated diseases such as Parkinson's disease, Huntington's disease, inflammatory bowel disease, rheumatoid arthritis, systemic lupus erythematosus, and primary Sjögren's syndrome. Current assessment tools rely heavily on self-reported questionnaires, which lack sensitivity to symptom fluctuations and impose burden on patients and researchers. Advances in digital health technologies now enable continuous monitoring of biophysiological, cognitive, physical, and social dimensions associated with these symptoms, potentially providing more reliable intermediate clinical endpoints for clinical trials.

Data Highlights

Disease CohortSample Size
Parkinson's Disease (PD)500
Huntington's Disease (HD)200
Inflammatory Bowel Disease (IBD)500
Rheumatoid Arthritis (RA)200
Systemic Lupus Erythematosus (SLE)200
Primary Sjögren's Syndrome (PSS)200
Healthy Volunteers (HV)200

Key Findings

  • The study includes 2000 participants across six chronic disease cohorts and healthy controls, recruited from 24 European sites.
  • Each participant undergoes four clinical visits with accompanying 7-day digital health technology (DHT) monitoring periods in their usual environment.
  • Sample size was determined to balance machine learning model training and evaluation needs, with at least 50 participants per cohort for psychometric validation.
  • Digital endpoints target four core symptom dimensions: biophysiology, cognitive performance, physical performance, and social behavior.
  • The study design received regulatory advice from the European Medicines Agency and ethics approvals at all sites.

Clinical Implications

This study protocol demonstrates a rigorous approach to developing objective, scalable digital biomarkers for fatigue and sleep-related symptoms in chronic diseases. The use of continuous digital monitoring may improve symptom assessment sensitivity and reliability, facilitating better patient management and more efficient clinical trials. Clinicians should anticipate future integration of such digital endpoints into routine practice and research.

Conclusion

The IDEA-FAST study represents a pioneering effort to leverage digital health technologies to objectively quantify fatigue, sleep quality, and daytime sleepiness across multiple chronic diseases. Its findings may transform symptom assessment and treatment development in these populations.

References

  1. IDEA-FAST Consortium 2023 -- Clinical Protocol for the IDEA-FAST Study

Original Source(s)

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