IDEA-FAST aims to identify digital biomarkers that assess fatigue, sleep, and activities in daily living in neurodegenerative disorders and immune-mediated inflammatory diseases. These digital endpoints are being identified for the following neurodegenerative diseases (NDD): Parkinson’s Disease (PD), Huntington’s Disease (HD), and for the following immune-mediated inflammatory diseases (IMID): Rheumatoid Arthritis (RA), Systemic Lupus Erythematosus (SLE), Primary Sjögren’s Syndrome (PSS), and Inflammatory Bowel Disease (IBD).

Fatigue and activities of daily living (ADL) are important for any successful therapeutic intervention. Current evaluations of ADL rely on subjective reports and questionnaires, which are prone to recall bias, reliability issues, and potentially long delays of months between reports. Through IDEA-FAST, we aim to identify these measures in an automatic and objective way.

The project is a large international undertaking, with 46 organisations across 15 countries. This includes pharmaceutical companies, academic & not-for-profit institutions, small-and-medium-sized enterprises, and patient organisations.

I am a Work Package lead for this project, responsible for the digital devices and technologies within the project. My main responsibilities relate to identifying technologies for the Clinical Observation Study, integration of these technologies, and ongoing support processes. This includes designing and performing a novel technology selection process that centralises patients and participants [1], ensuring selected technologies are acceptable to study participants [2], designing technologies and interactions with study participants [3], and supporting the exploration of qualification advice for novel cross-disease digital measures [4].

You can keep up-to-date with the progress of this project on the IDEA-FAST’s Project Site.


  1. Ieuan Clay et al. Reverse Engineering of Digital Measures: Inviting Patients to the Conversation. In: Digital Biomarkers 7.1 (2023), pp. 28-44. | DOI
  2. Johanna Graeber et al. Technology acceptance of digital devices for home use: Qualitative results of a mixed methods study. In: DIGITAL HEALTH 9 (2023). | DOI
  3. Jay Rainey et al. Data Contribution Summaries for Patient Engagement in Multi-Device Health Monitoring Research. In: UbiComp ‘21: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (2023), pp. 536-541. | DOI
  4. David Nobbs et al. Regulatory Qualification of a Cross-Disease Digital Measure: Benefits and Challenges from the Perspective of IMI Consortium IDEA-FAST. In: Digital Biomarkers 7.1 (2023), pp. 132–138. | DOI