Periodic Reporting for period 3 - RE-SAMPLE (RE-SAMPLE)
Periodo di rendicontazione: 2024-03-01 al 2025-08-31
Patients with Chronic Obstructive Pulmonary Disease (COPD) often also have other Complex Chronic Conditions (CCCs), like diabetes, depression or chronic heart failure. As these conditions have common risk factors and overlapping symptoms, this easily leads to delay of appropriate treatment. Flare ups (called ‘exacerbations’) of COPD and CCCs are detrimental to patient, health and social outcomes. Therefore it is important that patients receive timely care, which can prevent worsening of their disease(s), and that fits their personal needs and characteristics.
RE-SAMPLE aimed to answer upon the challenge of the increasing number of patients with Chronic Obstructive Pulmonary Disease (COPD) and Complex Chronic Conditions (CCCs) who require an integrated, personalised, and holistic approach to manage care. Our approach was to provide monitoring using Real World Data (RWD) and personalised predictions of CCC exacerbation risk, embedded in a multi-disciplinary virtual companionship programme offered to the patients (i.e. virtual companion) and the healthcare providers (i.e. active support programme) and supported by shared-care facilities for additional monitoring. RE-SAMPLE’s system architecture strictly followed privacy and security-by-design principles and used highly innovative secure multiparty computation techniques. The integrated CCC disease management thereby fits individual values and needs by continuous involvement of stakeholders, and our Pan-European service model facilitates deployment in different systems throughout Europe.
RE-SAMPLE aimed to answer upon the challenge of the increasing number of patients with Chronic Obstructive Pulmonary Disease (COPD) and Complex Chronic Conditions (CCCs) who require an integrated, personalised, and holistic approach to manage care. Our approach was to provide monitoring using Real World Data (RWD) and personalised predictions of CCC exacerbation risk, embedded in a multi-disciplinary virtual companionship programme offered to the patients (i.e. virtual companion) and the healthcare providers (i.e. active support programme) and supported by shared-care facilities for additional monitoring. RE-SAMPLE’s system architecture strictly followed privacy and security-by-design principles and used highly innovative secure multiparty computation techniques. The integrated CCC disease management thereby fits individual values and needs by continuous involvement of stakeholders, and our Pan-European service model facilitates deployment in different systems throughout Europe.
In the first 18 months of the project, we focused on building a strong foundation for the RE-SAMPLE platform and services in terms of a collective knowledge base and active end-user involvement, leading to definition of our functional specifications, platform architecture, release of our first functional prototype, and the start of an observational cohort study for RWD gathering.
In months 19-36, we focused on implementing the RE-SAMPLE features and models, defining our privacy and security measures, and building our final prototype. Furthermore, we focused on defining the contents of our Virtual Companionship programme (VCP) by defining the intervention and coaching strategies, as well as on the integration of the VCP as part of daily care and daily life by defining the integrated care protocols. Next, we started with the dissemination of project results to our stakeholders, by numerous scientific publications, workshops, and social media activities. Lastly, we shaped our business strategy using market analysis and are advancing our exploitation strategy.
In the last 18 months of the RE-SAMPLE project, we have accomplished the following main achievements to reach our project objectives.
- Our RE-SAMPLE platform was deployed and running in production in all three pilot sites since August 2024 till August 2025, continuously collecting the data and combined with the hospital and Healthentia data in the edge nodes. AI models were trained, and personalised risk predictions and AI-services for shared-care decision making were provided to the clinicians via the clinician dashboard. A comprehensive security and privacy-preserving framework was established and implemented that guided the system’s architecture and development throughout the project. Following a strict privacy- and security-by-design approach, the consortium updated organisational, legal, and technical requirements ensuring compliance with GDPR and ethical standards across diverse European healthcare contexts. We advanced privacy-preserving machine learning through the design and implementation of a federated learning prototype leveraging homomorphic encryption and differential privacy, effectively balancing data protection with computational efficiency.
- The virtual companionship programme (VCP) was integrated in daily care and evaluated with its stakeholders in terms of usability, acceptability and societal impact. The final VCP provides tailored care and support for patients with COPD and comorbidity by offering 1) a virtual companion for the patient for ongoing self-management support and personalised coaching, 2) a clinical dashboard where the healthcare professionals can assess data and predictions, do shared decision making and follow-up on the advice provided, and for use with shared-care facilities. The results indicate no significant change in flare-ups, but a positive patient engagement and significant behavioural changes. From a societal perspective, the VCP is profitable for the coalition of stakeholders. Our findings suggest that the VCP is both feasible and promising, though further analyses (e.g. on patient compliance, quality of life, healthcare utilisation) are necessary to fully evaluate its clinical and economic impact.
- We have ensured that our results, data, models, and software are openly available. Specific attention in this phase of the project was for the communication, dissemination and exploitation of the results, to ensure the uptake of our results also after our project’s end. There were numerous scientific publications, workshops, and social media activities and strategic focus on key exploitable results reflecting the need to align innovation management efforts with concrete exploitation pathways. We also ensured that our real-world data ecosystem (data and software) is available through open access, coupled with accessible guidelines.
In months 19-36, we focused on implementing the RE-SAMPLE features and models, defining our privacy and security measures, and building our final prototype. Furthermore, we focused on defining the contents of our Virtual Companionship programme (VCP) by defining the intervention and coaching strategies, as well as on the integration of the VCP as part of daily care and daily life by defining the integrated care protocols. Next, we started with the dissemination of project results to our stakeholders, by numerous scientific publications, workshops, and social media activities. Lastly, we shaped our business strategy using market analysis and are advancing our exploitation strategy.
In the last 18 months of the RE-SAMPLE project, we have accomplished the following main achievements to reach our project objectives.
- Our RE-SAMPLE platform was deployed and running in production in all three pilot sites since August 2024 till August 2025, continuously collecting the data and combined with the hospital and Healthentia data in the edge nodes. AI models were trained, and personalised risk predictions and AI-services for shared-care decision making were provided to the clinicians via the clinician dashboard. A comprehensive security and privacy-preserving framework was established and implemented that guided the system’s architecture and development throughout the project. Following a strict privacy- and security-by-design approach, the consortium updated organisational, legal, and technical requirements ensuring compliance with GDPR and ethical standards across diverse European healthcare contexts. We advanced privacy-preserving machine learning through the design and implementation of a federated learning prototype leveraging homomorphic encryption and differential privacy, effectively balancing data protection with computational efficiency.
- The virtual companionship programme (VCP) was integrated in daily care and evaluated with its stakeholders in terms of usability, acceptability and societal impact. The final VCP provides tailored care and support for patients with COPD and comorbidity by offering 1) a virtual companion for the patient for ongoing self-management support and personalised coaching, 2) a clinical dashboard where the healthcare professionals can assess data and predictions, do shared decision making and follow-up on the advice provided, and for use with shared-care facilities. The results indicate no significant change in flare-ups, but a positive patient engagement and significant behavioural changes. From a societal perspective, the VCP is profitable for the coalition of stakeholders. Our findings suggest that the VCP is both feasible and promising, though further analyses (e.g. on patient compliance, quality of life, healthcare utilisation) are necessary to fully evaluate its clinical and economic impact.
- We have ensured that our results, data, models, and software are openly available. Specific attention in this phase of the project was for the communication, dissemination and exploitation of the results, to ensure the uptake of our results also after our project’s end. There were numerous scientific publications, workshops, and social media activities and strategic focus on key exploitable results reflecting the need to align innovation management efforts with concrete exploitation pathways. We also ensured that our real-world data ecosystem (data and software) is available through open access, coupled with accessible guidelines.
In the final phases of our project, we gained insight in the progression of COPD and CCCs and continued building a body of knowledge beyond the state of the art and evidence for developing and providing AI-supported chronic care, with publications in renowned journals. For example, we observed that a deterioration of CHF symptoms precedes a next day's deterioration of COPD symptoms and vice versa. This highlights the importance to monitor the interplay between CCCs, if present, and act upon it to optimise patient disease management. From a technical perspective, e.g. AI models for the onset and progression of CCC exacerbations, and from the patient perspective, e.g. self-management strategies. All these insights are crucial for understanding the implications for further developing tailored interventions to manage COPD and CCCs.
Our efforts ensured that RE-SAMPLE’s decentralised real-world data ecosystem and RE-SAMPLE platform are secure, sustainable, and FAIR-compliant. To facilitate the impact of our results, guidelines for third parties are available for providing either controlled or open access to RE-SAMPLE datasets, synthetic data, trained machine learning models, and platform resources.
With RE-SAMPLE, we developed a new standard on how to tailor and implement predictive CCC care in which individuals benefit optimally by tailored CCC disease management. RE-SAMPLE significantly impacts towards this direction not only through the development of the platform and companionship programme, but also through its integration in the privacy-sensitive domain of healthcare, by healthcare organisations throughout Europe. Building this way forward, RE-SAMPLE can help alleviate the overall societal and economic burden of CCCs.
Our efforts ensured that RE-SAMPLE’s decentralised real-world data ecosystem and RE-SAMPLE platform are secure, sustainable, and FAIR-compliant. To facilitate the impact of our results, guidelines for third parties are available for providing either controlled or open access to RE-SAMPLE datasets, synthetic data, trained machine learning models, and platform resources.
With RE-SAMPLE, we developed a new standard on how to tailor and implement predictive CCC care in which individuals benefit optimally by tailored CCC disease management. RE-SAMPLE significantly impacts towards this direction not only through the development of the platform and companionship programme, but also through its integration in the privacy-sensitive domain of healthcare, by healthcare organisations throughout Europe. Building this way forward, RE-SAMPLE can help alleviate the overall societal and economic burden of CCCs.