Periodic Reporting for period 3 - 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: 2022-05-01 al 2023-04-30
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 the patients’ activities of daily living (ADL) and health-related quality of life (HRQoL). Current evaluations of ADL and HRQoL rely mainly on subjective reports, typically using standardized questionnaires provided by patients every few months. The approach is often prone to recall bias, reliability issues and poor sensitivity to change.
The advances in digital technology, data analytics and wearable devices provide unparalleled opportunities to identify digital correlates of ADL/HRQoL that are objective, reliable, quantifiable, individualized, can be used semi-continuously over prolonged periods of time and responsive to day to day variations, therefore, potentially more sensitive to change. These technologies allow more frequent recording (e.g. daily) of their self-scored health states in their habitual environment, often referred to as electronic PRO (ePRO).
The objective of IDEA-FAST is to identify digital endpoints that provide reliable, objective and sensitive evaluation of ADL/disability/HRQoL relevant 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 advances in digital technology, data analytics and wearable devices provide unparalleled opportunities to identify digital correlates of ADL/HRQoL that are objective, reliable, quantifiable, individualized, can be used semi-continuously over prolonged periods of time and responsive to day to day variations, therefore, potentially more sensitive to change. These technologies allow more frequent recording (e.g. daily) of their self-scored health states in their habitual environment, often referred to as electronic PRO (ePRO).
The objective of IDEA-FAST is to identify digital endpoints that provide reliable, objective and sensitive evaluation of ADL/disability/HRQoL relevant 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).
Within Period 1 IDEA-FAST undertook a Feasibility Study the aims of which are to: (i) identify the most promising digital measures of fatigue and sleep; (ii) test the feasibility, acceptability and utility of the various digital technologies that will be used to profile sleep, fatigue and ADLs in the various patient populations.
To prepare for the study a number of measuring devices for use across the disease cohorts were evaluated against a defined selection criteria. To support their use and provide a pipeline to transfer data to the Data Management Platform methods for data transfer were documented and API’s developed. A first version of the Data Management Platform (DMP) has been developed and released which includes Access Control and data provenance mechanisms for compliance with legal and data privacy requirements (e.g. GDPR), and to ensure data integrity and security.
The FS study protocol has been developed and ethics approval gained, this includes a model of informed consent. The COVID pandemic has impacted patient recruitment. The involvement and engagement with patients and patients groups has been embedded within the feasibility study. A Patient Specialist Advisory Board (PSAB) and the Patient Involvement and Engagement (PIE) group have been setup to enable this.
The assessment protocol for device-specific digital endpoints and candidate digital endpoints for fatigue, sleep disturbances and other ADL and HRQoL measures in NDD and IMID) have been completed and all required candidate digital endpoints are available.
A regulatory strategy has been developed which led to the submission to the EMA requesting qualification advice.
Within Period 2 IDEA-FAST has completed the FS plus a supplementary polysomnography (PSG) sub-study. These have generated 2 multi-modal data sets, likely unique in their form. To our knowledge, this is the largest dataset with this comprehensive study design worldwide. The data from both studies was analysed to develop an understanding of relevant candidate digital endpoints and their variability in the home environment. The output of the feasibility study and the data analysis have supported the development of the study protocol for the Clinical Observational Study (COS) which has achieved ethics and sponsor approval. Recruitment to the COS is due to begin in the summer of 2022. A significant amount of work has been focused on the preparation of the COS. This has included developing an understanding of the requirements of digital sensors at site levels together with the logistics required to procure and deliver these devices to 22 study sites across 10 European countries.
Work has also been undertaken to map exploitable assets generated within IDEA-FAST so that they can be fully exploited. In addition to this the project has disseminated to it stakeholder base through the website, LinkedIn and twitter as well as via peer reviewed publications and presentations.
Within Period 3, the consortium has obtained the necessary regulatory approvals to start recruitment to the COS, and has made steady progress with nearly 500 participants recruited. To increase the impact of the FS, we have performed additional analyses of the FS data and shared the learnings from these through presentations at appropriate national and international conferences, multi-stakeholder workshops and publications in peer-reviewed scientific journals. Furthermore, we have developed a new mobile application and improved an existing mobile application to capture socialisation and neurocognitive data respectively with extensive patient and public engagement. To support the data collection and management of the project studies, a clinical database and a Data Management Platform (DMP) have been developed, and a data transfer and integration pipeline has been established between the two platforms.
To prepare for the study a number of measuring devices for use across the disease cohorts were evaluated against a defined selection criteria. To support their use and provide a pipeline to transfer data to the Data Management Platform methods for data transfer were documented and API’s developed. A first version of the Data Management Platform (DMP) has been developed and released which includes Access Control and data provenance mechanisms for compliance with legal and data privacy requirements (e.g. GDPR), and to ensure data integrity and security.
The FS study protocol has been developed and ethics approval gained, this includes a model of informed consent. The COVID pandemic has impacted patient recruitment. The involvement and engagement with patients and patients groups has been embedded within the feasibility study. A Patient Specialist Advisory Board (PSAB) and the Patient Involvement and Engagement (PIE) group have been setup to enable this.
The assessment protocol for device-specific digital endpoints and candidate digital endpoints for fatigue, sleep disturbances and other ADL and HRQoL measures in NDD and IMID) have been completed and all required candidate digital endpoints are available.
A regulatory strategy has been developed which led to the submission to the EMA requesting qualification advice.
Within Period 2 IDEA-FAST has completed the FS plus a supplementary polysomnography (PSG) sub-study. These have generated 2 multi-modal data sets, likely unique in their form. To our knowledge, this is the largest dataset with this comprehensive study design worldwide. The data from both studies was analysed to develop an understanding of relevant candidate digital endpoints and their variability in the home environment. The output of the feasibility study and the data analysis have supported the development of the study protocol for the Clinical Observational Study (COS) which has achieved ethics and sponsor approval. Recruitment to the COS is due to begin in the summer of 2022. A significant amount of work has been focused on the preparation of the COS. This has included developing an understanding of the requirements of digital sensors at site levels together with the logistics required to procure and deliver these devices to 22 study sites across 10 European countries.
Work has also been undertaken to map exploitable assets generated within IDEA-FAST so that they can be fully exploited. In addition to this the project has disseminated to it stakeholder base through the website, LinkedIn and twitter as well as via peer reviewed publications and presentations.
Within Period 3, the consortium has obtained the necessary regulatory approvals to start recruitment to the COS, and has made steady progress with nearly 500 participants recruited. To increase the impact of the FS, we have performed additional analyses of the FS data and shared the learnings from these through presentations at appropriate national and international conferences, multi-stakeholder workshops and publications in peer-reviewed scientific journals. Furthermore, we have developed a new mobile application and improved an existing mobile application to capture socialisation and neurocognitive data respectively with extensive patient and public engagement. To support the data collection and management of the project studies, a clinical database and a Data Management Platform (DMP) have been developed, and a data transfer and integration pipeline has been established between the two platforms.
IDEA-FAST aims to build a clinically valid digital fatigue and sleep disturbances assessment system that is uniformly applicable across six chronic diseases. with the possibility to also identify disease-specific ADL digital signatures of these symptoms. In NDD digital endpoints are expected to reliably assess circadian changes in severity and disease progression over 1 year. Thus accurate assessment of fatigue 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 – Analysis using extant data for validation of potential algorithms to provide digital biomarkers for the diseases of interest in the project.
3 – Development and implementation of a clinical Feasibility Study (FS) to evaluate the sensors and algorithms
4 – Development of a data pipeline and Data Management Platform (DMP) to enable the study and allow sharing of data.
5 – Informal qualification advice received from EMA.
6 - Completed the FS (146 patients, 6 disease and healthy controls) and supplementary polysomnography sub-study
7 - Generated 2 unique multi-modal data sets with multiple digital devices in combination with demographic/clinical parameters and qualitative data in disease cohorts. To our knowledge, this is the largest dataset with this comprehensive study design worldwide.
8 - Analysed the data from the FS
9 - Further development of the DMP
10 - Developed the study protocol for the Clinical Observational Study (COS), which has achieved ethics and sponsor approval, from the FS results
11 - Started recruitment of the COS - currently 500 patient recruited
12 - Supported the EMA qualification advice process and received feedback with the FS result data.
13 - Developed a clinical database and data transfer to the DMP
14 - Developed app to capture socialisation and neurocognitive data
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 – Analysis using extant data for validation of potential algorithms to provide digital biomarkers for the diseases of interest in the project.
3 – Development and implementation of a clinical Feasibility Study (FS) to evaluate the sensors and algorithms
4 – Development of a data pipeline and Data Management Platform (DMP) to enable the study and allow sharing of data.
5 – Informal qualification advice received from EMA.
6 - Completed the FS (146 patients, 6 disease and healthy controls) and supplementary polysomnography sub-study
7 - Generated 2 unique multi-modal data sets with multiple digital devices in combination with demographic/clinical parameters and qualitative data in disease cohorts. To our knowledge, this is the largest dataset with this comprehensive study design worldwide.
8 - Analysed the data from the FS
9 - Further development of the DMP
10 - Developed the study protocol for the Clinical Observational Study (COS), which has achieved ethics and sponsor approval, from the FS results
11 - Started recruitment of the COS - currently 500 patient recruited
12 - Supported the EMA qualification advice process and received feedback with the FS result data.
13 - Developed a clinical database and data transfer to the DMP
14 - Developed app to capture socialisation and neurocognitive data