Periodic Reporting for period 5 - IDEA-FAST (Identifying Digital Endpoints to Assess FAtigue, Sleep and acTivities in daily living in Neurodegenerative disorders and Immune-mediated inflammatory diseases)
Periodo di rendicontazione: 2024-05-01 al 2025-04-30
For patients with chronic diseases such as neurodegenerative disorders (NDD) and immune-mediated inflammatory diseases (IMID), a key attribute for any successful therapeutic intervention is its ability to improve patients’ activities of daily living (ADL) and health-related quality of life (HRQoL). Fatigue and sleep problems are among the most disabling symptoms identified by patients that affect their ADL/HRQoL. Current evaluations of fatigue and sleep problems rely mainly on subjective reports provided by patients. The approach is often prone to recall bias, reliability issues and poor sensitivity to change. It can also be burdensome to patients. Advances in digital technology, data analytics and wearable devices provide unparalleled opportunities to identify digital correlates of fatigue and sleep problems that are objective, reliable, quantifiable, individualized, can be used semi-continuously over prolonged periods of time in the patients' home environment, and are responsive to day to day variations, and thus potentially more sensitive to change.
The objective of IDEA-FAST is to identify digital endpoints that provide reliable, objective and sensitive evaluation of fatigue and sleep problems for the following NDD: Parkinson's disease (PD), Huntington's disease (HD) and the following IMID: Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjögren's syndrome (PSS), and inflammatory bowel disease (IBD).
The objective of IDEA-FAST is to identify digital endpoints that provide reliable, objective and sensitive evaluation of fatigue and sleep problems for the following NDD: Parkinson's disease (PD), Huntington's disease (HD) and the following IMID: Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjögren's syndrome (PSS), and inflammatory bowel disease (IBD).
In Period 1 (P1), IDEA-FAST conducted a Feasibility Study (FS) to: (i) identify the most promising digital measures of fatigue and sleep; (ii) test the feasibility, acceptability and utility of the various digital technologies for profiling sleep, fatigue and ADLs in the various patient populations. The FS study protocol was co-developed with patients, and regulatory approvals were obtained. A first version of the Data Management Platform (DMP) was developed and released which included Access Control and data provenance mechanisms for compliance with legal & data privacy requirements, and to ensure data integrity and security. The assessment protocol for candidate digital endpoints of fatigue and sleep problems in NDD and IMID was prepared. A regulatory strategy was developed and discussed with the EMA Innovation Task Force. The consortium governance structure and various advisory boards were established. A project website and social media platforms were created.
In P2, IDEA-FAST completed the FS plus a supplementary polysomnography (PSG) sub-study. The 2 multi-modal datasets were among the largest datasets worldwide with such comprehensive study design. The data was analysed to identify candidate digital endpoints and their variability in the home environment. The results supported the development of the study protocol for the Clinical Observational Study (COS) which received regulatory approvals. In preparation for the participant recruitment to the COS, a strategy for procurement and distribution of digital technology to 22 study sites across 10 European countries was developed. Work was also undertaken to map potential exploitable assets generated within IDEA-FAST. In addition, the project disseminated to its stakeholders through the website, LinkedIn and X as well as via peer reviewed publications and presentations.
In P3, IDEA-FAST initiated recruitment to the COS, with nearly 500 participants recruited. To increase the impact of the FS, we performed additional analyses of the FS data and disseminated the results at appropriate conferences and in peer-reviewed scientific journals. With extensive patient and public engagement, we developed a new mobile application and improved an existing mobile application to capture socialisation and neurocognitive data, respectively. To support the data collection and management, a clinical database was developed, the DMP was further refined, and a data transfer and integration pipeline was established between the two platforms.
In P4, IDEA-FAST continued recruitment to the COS and various mitigation actions were implemented to overcome delays due to COVID. Effort was focused on ensuring the quality, completeness and standardisation of the COS data being collected. The COS Statistical Analysis Plan (SAP) was generated. An Analytical Environment for the DMP was developed and several data analytics pipelines have been deployed. A 12-month project extension was requested and granted. Two new partners (Bristol-Myers-Scribbs (EFPIA) and University College Cork (academic) have joined the consortium.
In P5, IDEA-FAST continued recruitment to the COS with 1,700 participants (out of a target of 2,000) recruited. Significant data analysis has been undertaken including feature extraction and performance assessment of candidate device-specific digital endpoints. The DMP was further refined. Work on the data governance strategy has continued in light of the upcoming EHDS regulations. An interim exploitation plan was produced.
In P2, IDEA-FAST completed the FS plus a supplementary polysomnography (PSG) sub-study. The 2 multi-modal datasets were among the largest datasets worldwide with such comprehensive study design. The data was analysed to identify candidate digital endpoints and their variability in the home environment. The results supported the development of the study protocol for the Clinical Observational Study (COS) which received regulatory approvals. In preparation for the participant recruitment to the COS, a strategy for procurement and distribution of digital technology to 22 study sites across 10 European countries was developed. Work was also undertaken to map potential exploitable assets generated within IDEA-FAST. In addition, the project disseminated to its stakeholders through the website, LinkedIn and X as well as via peer reviewed publications and presentations.
In P3, IDEA-FAST initiated recruitment to the COS, with nearly 500 participants recruited. To increase the impact of the FS, we performed additional analyses of the FS data and disseminated the results at appropriate conferences and in peer-reviewed scientific journals. With extensive patient and public engagement, we developed a new mobile application and improved an existing mobile application to capture socialisation and neurocognitive data, respectively. To support the data collection and management, a clinical database was developed, the DMP was further refined, and a data transfer and integration pipeline was established between the two platforms.
In P4, IDEA-FAST continued recruitment to the COS and various mitigation actions were implemented to overcome delays due to COVID. Effort was focused on ensuring the quality, completeness and standardisation of the COS data being collected. The COS Statistical Analysis Plan (SAP) was generated. An Analytical Environment for the DMP was developed and several data analytics pipelines have been deployed. A 12-month project extension was requested and granted. Two new partners (Bristol-Myers-Scribbs (EFPIA) and University College Cork (academic) have joined the consortium.
In P5, IDEA-FAST continued recruitment to the COS with 1,700 participants (out of a target of 2,000) recruited. Significant data analysis has been undertaken including feature extraction and performance assessment of candidate device-specific digital endpoints. The DMP was further refined. Work on the data governance strategy has continued in light of the upcoming EHDS regulations. An interim exploitation plan was produced.
IDEA-FAST aims to develop clinically valid cross-disease digital biomarkers of fatigue and sleep problems, with the possibility to also identify disease-specific ADL digital signatures of these symptoms. The accurate assessment of fatigue and sleep problems will add a new dimension beyond the current assessment tools available for these diseases, enabling a more complete/comprehensive assessment of these conditions.
Within the project the following key advances beyond the state of the art have been achieved:
1 – Assessment of sensor types and devices for use with patients to capture data on fatigue and sleep
2 – Completion of the FS (146 patients, 6 disease cohorts and healthy controls) and supplementary polysomnography sub-study to evaluate the sensors and algorithms
3 – Development of a data pipeline, DMP and Analytical Environment to enable the study and allow controlled data access
4 – Informal qualification advice received from EMA based on FS result data
5 – Created 2 large, unique multi-modal datasets with multiple digital devices in combination with demographic/clinical parameters and qualitative data in disease cohorts
6 – Analysed the FS data and identified candidate digital biomarkers of fatigue
7 – Developed the protocol for the COS
8 – Obtain support from the EMA SAWP on the COS study design
9 – Recruited 1704 participants (>85% of target) to the COS
10 – Developed a clinical database and data transfer pipelines to the DMP
11 – Developed app to capture socialisation and neurocognitive data
12 – Implemented automated algorithms for checking data quality and completeness
13 – Performed initial analysis of COS data including feature extraction and performance assessment of candidate device-specific digital endpoints
14 – Develop a strategy for exploitation, sustainability and impact of the project assets.
15 – Created a network of clinical sites with expertise to conduct complex clinical trials involving digital health technologies
16 – Created a consortium of multidisciplinary expertise (including patient partners) in the use of digital technology to evaluate the impact of ADL/HRQoL in chronic disease
Within the project the following key advances beyond the state of the art have been achieved:
1 – Assessment of sensor types and devices for use with patients to capture data on fatigue and sleep
2 – Completion of the FS (146 patients, 6 disease cohorts and healthy controls) and supplementary polysomnography sub-study to evaluate the sensors and algorithms
3 – Development of a data pipeline, DMP and Analytical Environment to enable the study and allow controlled data access
4 – Informal qualification advice received from EMA based on FS result data
5 – Created 2 large, unique multi-modal datasets with multiple digital devices in combination with demographic/clinical parameters and qualitative data in disease cohorts
6 – Analysed the FS data and identified candidate digital biomarkers of fatigue
7 – Developed the protocol for the COS
8 – Obtain support from the EMA SAWP on the COS study design
9 – Recruited 1704 participants (>85% of target) to the COS
10 – Developed a clinical database and data transfer pipelines to the DMP
11 – Developed app to capture socialisation and neurocognitive data
12 – Implemented automated algorithms for checking data quality and completeness
13 – Performed initial analysis of COS data including feature extraction and performance assessment of candidate device-specific digital endpoints
14 – Develop a strategy for exploitation, sustainability and impact of the project assets.
15 – Created a network of clinical sites with expertise to conduct complex clinical trials involving digital health technologies
16 – Created a consortium of multidisciplinary expertise (including patient partners) in the use of digital technology to evaluate the impact of ADL/HRQoL in chronic disease