QUALITOP | Monitoring multidimensional aspects of QUAlity of Life after cancer ImmunoTherapy - an Open smart digital Platform for personalized prevention and patient management

Summary
"Cancer immunotherapy brought about significant progress in cancer treatment. It resulted in high efficacy in some cancers; e.g., up to 60% objective response rate in melanoma and 80% complete response rate in acute lymphoblastic leukaemia. Nevertheless, two main challenges still impede improving cancer patients’ health status and quality of life (QoL) after immunotherapy initiation: 1) a crucial need for “predictive markers” of occurrence of immunotherapy-related adverse events (IR-AEs) to predict and improve patients’ health status and promote their QoL; and, 2) the lack of knowledge on patients after start of immunotherapy outside randomised controlled trials. To reach these goals, significantly more diversified sources of data are required.
Project QUALITOP aims at developing a European immunotherapy-specific open Smart Digital Platform and using big data analysis, artificial intelligence, and simulation modelling approaches. This will enable collecting and aggregating efficiently real-world data to monitor health status and QoL of cancer patients given immunotherapy. Through causal inference analyses, QUALITOP will identify the determinants of health status regarding IR-AEs and define patient profiles in a real-world context. For this, heterogeneous data sources (big data), both retrospective and prospective --collected for QUALITOP from clinical centres in four EU countries—will integrate lifestyle, genetic, and psychosocial determinants of QoL. Using machine learning approaches, QUALITOP will provide ""real-time"" recommendations stemming from patient profiles and feedbacks via the Smart Digital Platform. Furthermore, an increased visibility on patients’ behaviour, a better IR-AEs prediction, and an improvement of care coordination will help analysing through simulation modelling approaches the gain in cost-effectiveness. Guidelines will be issued over the short and long-term.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/875171
Start date: 01-01-2020
End date: 30-06-2024
Total budget - Public funding: 5 196 772,00 Euro - 5 196 772,00 Euro
Cordis data

Original description

"Cancer immunotherapy brought about significant progress in cancer treatment. It resulted in high efficacy in some cancers; e.g., up to 60% objective response rate in melanoma and 80% complete response rate in acute lymphoblastic leukaemia. Nevertheless, two main challenges still impede improving cancer patients’ health status and quality of life (QoL) after immunotherapy initiation: 1) a crucial need for “predictive markers” of occurrence of immunotherapy-related adverse events (IR-AEs) to predict and improve patients’ health status and promote their QoL; and, 2) the lack of knowledge on patients after start of immunotherapy outside randomised controlled trials. To reach these goals, significantly more diversified sources of data are required.
Project QUALITOP aims at developing a European immunotherapy-specific open Smart Digital Platform and using big data analysis, artificial intelligence, and simulation modelling approaches. This will enable collecting and aggregating efficiently real-world data to monitor health status and QoL of cancer patients given immunotherapy. Through causal inference analyses, QUALITOP will identify the determinants of health status regarding IR-AEs and define patient profiles in a real-world context. For this, heterogeneous data sources (big data), both retrospective and prospective --collected for QUALITOP from clinical centres in four EU countries—will integrate lifestyle, genetic, and psychosocial determinants of QoL. Using machine learning approaches, QUALITOP will provide ""real-time"" recommendations stemming from patient profiles and feedbacks via the Smart Digital Platform. Furthermore, an increased visibility on patients’ behaviour, a better IR-AEs prediction, and an improvement of care coordination will help analysing through simulation modelling approaches the gain in cost-effectiveness. Guidelines will be issued over the short and long-term.
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Status

SIGNED

Call topic

SC1-DTH-01-2019

Update Date

26-10-2022
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Horizon 2020
H2020-EU.3. SOCIETAL CHALLENGES
H2020-EU.3.1. SOCIETAL CHALLENGES - Health, demographic change and well-being
H2020-EU.3.1.3. Treating and managing disease
H2020-EU.3.1.3.2. Transferring knowledge to clinical practice and scalable innovation actions
H2020-SC1-DTH-2019
SC1-DTH-01-2019 Big data and Artificial Intelligence for monitoring health status and quality of life after the cancer treatment
H2020-EU.3.1.5. Methods and data
H2020-EU.3.1.5.1. Improving halth information and better use of health data
H2020-SC1-DTH-2019
SC1-DTH-01-2019 Big data and Artificial Intelligence for monitoring health status and quality of life after the cancer treatment