Identifying Digital Endpoints For Fatigue To Drive Better Clinical Care And Treatments
By Michele Veldsman, Ph.D., member of IDEA-FAST & director of neuroscience, Cambridge Cognition
Fatigue, a medical complaint that has confounded medical professionals and researchers for decades, conceals a profoundly challenging journey for those burdened by its effects. Chronic and severe exhaustion inflicts debilitating consequences, casting a shadow over the lives of countless individuals. Regrettably, pursuing medical understanding and effective treatment often proves futile, leaving those affected feeling marginalized and misunderstood. This frustration is further exacerbated by mistrust and skepticism from the medical community and society toward this condition.
The U.S. Department of Health & Human Services estimates that as many as 23 million Americans may have developed long COVID-19 since the pandemic started.1 More than 17 million people in Europe also have reported symptoms2, with fatigue the most persistent. Fatigue isn’t confined to long COVID; it spans a broad spectrum of diseases, from neurodegenerative disorders such as Parkinson’s disease (PD) and Huntington’s disease (HD) to inflammatory conditions like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). It also can manifest without any known underlying health conditions. Yet, despite the staggering number of sufferers, doubt about the legitimacy of the condition persists.3
The struggle to achieve recognition and acceptance of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) has been arduous. A significant obstacle in securing medical acknowledgement of fatigue is the lack of comprehensive and accurate biomarkers.
Unravelling The Diagnostic Challenge Of Fatigue
Unlike medical conditions with clear diagnostic tests, such as diabetes, fatigue is challenging to define. The absence of clear biological indicators makes diagnosing and finding effective treatments difficult. Some people may be able to point to low iron and vitamin D levels as reasons for their fatigue, making it easier to understand and treat. But for those without such markers, the situation becomes frustrating. They may be wrongly thought to have fatigue from sleep problems or depression. Although fatigue, poor sleep, and depression often co-occur, fatigue can, and often does, exist independently.
The current state of biomarkers for fatigue is marred by deficiencies that pose challenges in comprehending and diagnosing this complex condition. One major problem is a lack of precision; existing biomarkers often cannot distinguish fatigue from other factors, rendering them unreliable as stand-alone indicators. Fatigue is typically measured via self-reporting symptoms over the previous few days or weeks. This method is subject to recall bias and fails to capture variability or fluctuations in symptoms. Critically, the lack of measures of fatigue that sensitively capture changes over time impedes the development of treatments where an apparent change in outcome is required to show efficacy. Fatigue’s multifaceted nature and the interplay of biological, psychological, and environmental factors that underlie it add to this complexity.
A more reliable and specific set of biomarkers is required to enhance our understanding and improve diagnostics and treatments for those living with fatigue. To bring hope to finding better tools and measurement methodologies, a new pan-European consortium has been established.
Finding Digital Endpoints With IDEA-FAST
IDEA-FAST is a pioneering collaborative effort under the Innovative Medicines Initiative. This consortium brings together an alliance of 46 partners spanning 15 countries, including academic institutions, nonprofit organizations, patient groups, pharmaceutical companies, and technology partners. Their collective mission is to develop digital biomarkers for fatigue and sleep disturbances and track their relationship to activities of daily living and health-related quality of life. The study will involve the recruitment of 2,000 patients with neurodegenerative conditions like Huntington’s and Parkinson’s disease, as well as individuals with immune-mediated inflammatory diseases such as IBD, primary Sjogren’s syndrome, rheumatoid arthritis, and systemic lupus erythematosus.
IDEA-FAST aims to identify a set of digital endpoints and corresponding digital technologies that provide a reliable, objective, and sensitive evaluation of fatigue and sleep disturbances for clinical validation. It is hoped that these measures will mirror patients’ actual experiences and provide sensitive markers that capture daily fluctuations in symptoms in their natural living environment. Not only will this allow patients to have an objective marker that reflects their experience, but it also will critically provide a way to test if treatments are effective in changing this marker. It will be a significant step toward life-improving therapies.
The study aims to uncover insights into the commonalities and differences in how fatigue affects individuals with diverse medical conditions. For instance, does the experience of fatigue align between a rheumatoid arthritis patient and a Parkinson’s patient? Is morning fatigue akin to post-exertion fatigue? Could a treatment effective for a Huntington’s disease patient also benefit someone with IBD?
As part of its research, the consortium will use brief, high-frequency cognitive testing delivered through patients’ smartphones as objective markers of fatigue and sleep disturbances. In addition to undergoing cognitive testing twice daily, patients will be asked to report their mood, sleep quality, sleepiness, and levels of physical and mental fatigue on a sliding scale using the touch screen feature on their mobile device. This solution has garnered recognition from the European Commission’s Innovation Radar as a testament to its innovation.
It is hoped that sensitive measures of cognitive performance in these tests might track fluctuations in self-reported mental and physical fatigue. The hope is that patients will no longer struggle to express their feelings of fatigue and will have objective markers to reflect their experience.
The IDEA-FAST study is anticipated to conclude in mid-2025. Data sharing among consortium partners will be facilitated through a customized data management platform. Access to the data will require submitting an application to the consortium, and certain subsets of the data will be made open access, subject to agreement within the consortium.
Defining Fatigue For Better Therapies
Fatigue is a huge health challenge, with many patients affected worldwide. Correctly identifying and understanding fatigue is a challenge for healthcare providers and drug developers, not to mention a frustrating journey for patients. A scarcity of practical tools for measuring changes in a patient’s fatigue condition means it is difficult to assess the efficacy of novel treatments reliably.
The number of partners that have already signed up to be part of the IDEA-FAST consortium demonstrates the magnitude of the problem. The emergence of the consortium offers a promising avenue, bringing together partners from medical, academic, technology, and pharmaceutical companies to uncover digital biomarkers for fatigue. This development holds the potential for a deeper understanding of the condition, paving the way for improved treatment qualification and giving hope to those who struggle with fatigue’s burden.
References:
- https://www.hhs.gov/about/news/2023/07/31/hhs-announces-formation-office-long-covid-research-practice-launch-long-covid-clinical trials-through-recover-initiative.html
- https://www.who.int/europe/news-room/fact-sheets/item/post-covid-19-condition
- https://www.theatlantic.com/health/archive/2020/08/long-haulers-covid-19-recognition-support-groups-symptoms/615382/n`
About The Author:
Michelle Veldsman, Ph.D., is director of neuroscience R&D for Cambridge Cognition, one of the technology partners in the IDEA-FAST consortium. Her work in the consortium seeks to find digital cognitive biomarkers of fatigue and sleep disturbances, relating daily fluctuations in self-reported fatigue and sleep to performance in attention, memory, and executive function tasks. She has a Ph.D. in cognitive neuroscience from the University of Cambridge and 15 years of academic neuroscience experience in cognitive neurology.