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Oncology is a highly evidence-based speciality and cancer data are critical to treatment planning. However, as precision medicine capabilities grow, those decisions likely will become more complex. PERSIST aim to show the potential of big data technology for making fundamental changes in care delivery for cancer survivors.

Security of health data

PERSIST will advance the maturity level of existing algorithms that estimate the risk of reidentification in anonymized datasets contributing to increase the confidence of EU citizens when deciding to contribute their health data for secondary purposes.

AI & Big Data

PERSIST aim to show the potential of big data technology for making fundamental changes in care delivery for cancer survivors.

Improved health care

PERSIST enables, for the first time, a more complete and frequent update of the survivorship care plans based on the aggregation and processing of real-time prospective data altogether with existing retrospective data.

New scientific research

PERSIST big data model will contribute to create entirely new knowledge and understanding on how patient behaviours and various patient-specific co-morbidities may influence health outcomes.

Core technological and organizational challenges

PERSIST can help especially to the health services like patient-reported outcomes, patient satisfaction scoring, identifying high-risk patients and giving them the appropriate treatment, and supporting patients who are either at high risk of reoccurrence.

One of the biggest challenges for the establishment of a digital open market of health data from which researchers can develop new technologies/therapies is the trust on privacy. PERSIST will advance the maturity level of existing algorithms that estimate the risk of reidentification in anonymized datasets (developed by GRAD under the EU project WITDOM) contributing to increase the confidence of EU citizens when deciding to contribute their health data for secondary purposes.
Another of the biggest bottlenecks and challenges is the difficulty to co-create a solution involving the different actors within the same project to relieve the potential of the big data analytics era. PERSIST will provide co-creation activities by involving partners from different countries, with different expertise (clinical side, technical side) and different organizational types will come together for bringing all their experiences about big data and cancer treatment to achieve a common goal.
PERSIST will foster the transition to new computational, statistical, and other mathematical methods of analysis that enable the integration of data -one of the biggest challenge of big data- across the multiple scales of time and space typical of complex biological systems in their healthy and diseased states.
PERSIST will demonstrate in a controlled clinical study with 160 survivors the potential of prescriptive analytics automatically to synthesize big data and provide advice on a number of different possible outcomes before the decisions are actually made. The decision maker can take this information to execute and personalise the care plan.
PERSIST will prepare two highly convincing use cases for breast and colorectal cancer survivors to test the routine clinical care impact and widespread the specific impact of Big Data technologies for two cancer types with the highest rates of survival.

Market change motivation

To alleviate the rising cost pressure, payers are demanding more robust evidence of therapies, leading to the stratification. It is no longer the case that one treatment is necessarily suitable for all patients. Advances in science and technology platforms are likely to progress faster in oncology than in other disease areas, due to terminal disease prevalence and the corresponding increase in patients’ risk appetite. In a changing world, where innovation enables patients to access information and insights more readily than ever before, they will fast become the most relevant stakeholder in the healthcare ecosystem, thus conferring the need for a change in emphasis from other players in the system.

Consortium

Gradiant is a Research & Tecnology Organization (RTO) focused on connectivity, intelligence and security technologies.
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Servizo Galego de Saúde (SERGAS), the Galician healthcare service, is responsible for the management and provision of public health services in the National Health Care system in Galicia.
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Dedalus is the world’s leading independent, end-to-end IT services and solutions company, helping clients harness the power of innovation to thrive on change.
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Emoda Software is a research and development company which is located in IYTE University Technopark.
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The University of Maribor is developing new fields, testing new teaching and learning methods and constantly searching for new methods of cooperation with its environment.
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University Medical Centre Maribor is a public healthcare institution, providing secondary and tertiary healthcare service in north-eastern Slovenia.
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The University of Applied Sciences and Arts Western Switzerland (HES-SO) is the largest University of Applied Sciences and the second largest higher education institution in Switzerland.
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University of Latvia (UL) with its 14 000 students, 13 faculties and more than 13 research institutes is one of the largest comprehensive and leading research universities in the Baltic States.
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CyberEthics Lab (CEL) is a start-up Italian SME leveraging on the experience and knowledge of its multidisciplinary core members.
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The CHU Liège is the academic hospital linked to the University of Liège and the only university hospital in Wallonia Region (Belgium).
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Symptoma offers its services to doctors, hospitals, medtech/pharma/insurance companies, and governments.
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RUBYnanomed was founded in 2018 as a spin-off of INL and aims to bring lab discoveries to the clinical market.
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The National Patients’ Organisation was established in January 2010 in Bulgaria as an association of legal entities – patient organizations.
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For patients

Expected impacts for the cancer survivors

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For professionals

Expected impact for the practitioners

Expected Impact: Emerging data-driven analytics and advanced simulation methods to study causal mechanisms and improve forecasts of ill-health, identification of disease trajectories and relapse.

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Supporters

The knowledge and expertise of the consortium are strengthened by the support of collaborating entities – companies, universities and organizations, who help the project enlarge its focus and achieve better results.

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