Summary
Cancer is a leading cause of death in the EU, and the number of people dying of the disease is expected to rise by a quarter between now and 2035. Today, cancer patients generate a wealth of data as they move along the care pathway, ranging from scans and pathology reports to electronic health records and patient-reported outcomes. If this data could be linked up and analysed, it could both dramatically improve patient care and contribute to research; however, doing this in practice is far from easy. Meanwhile artificial intelligence (AI) tools to improve care exist, but integrating them into care remains challenging.
The aim of PATH is to transform cancer care by drawing on secure data exchange and digital technologies to integrate AI tools into care.
To do this, the project will first map the state of the art in terms of the AI tools available, study existing best practice for their integration into care pathways, and analyse the barriers to their wider adoption. They will then take existing AI tools provided by the project partners and enhance and adapt them for use in the clinic. When working on the tools, they will ensure that the models are based on data from diverse patient populations to avoid bias. They will also promote algorithms that are aligned with the FAIR (findable, accessible, interoperable, reusable) data principles. Finally, the PATH team will ensure AI models adhere to the principles of trustworthy AI.
A key project output will be the PATH dashboard and accompanying data space. With an intuitive, interactive user interface, the dashboard will allow health professionals to easily select, deploy and interact with AI tools, enabling seamless integration into daily medical practice. The project will continuously collect feedback from both healthcare professionals and patients to improve the platform and the AI solutions it hosts.
The project will validate the system in large-scale pilot studies in hospitals, oncology centres and patient organisations across the EU. By testing AI-powered decision support in these real-world settings, the project will generate best practices for AI adoption in healthcare.
A core element of PATH is its strong co-creation approach with end users, including healthcare professionals, patient organisations, and policymakers. This collaborative process will support the development of relevant best practices, guidelines, and comprehensive training materials, ultimately facilitating the responsible and sustainable adoption of AI across the healthcare sector.
Ultimately, the project outputs will provide health professionals with validated AI tools that can be deployed across diagnosis, treatment, and long-term patient management. Patients will gain personalised AI-driven insights, empowering informed healthcare decisions. For their part, AI developers will benefit from FAIR data exchange, allowing the large-scale validation of new AI-based tools.
The project also contributes to the implementation of key EU policies, such as the Beating Cancer Plan and the European Health Data Spaces (EHDS).
Participants
Show participants on mapCOCIR
- Ancora Health BV, Groningen, NetherlandsSME
Universities, research organisations, public bodies, non-profit groups
- Aristotelio Panepistimio Thessalonikis, Thessaloniki, Greece
- Centro Regionale Information E Communication Technology Scrl, Benevento, Italy
- Ethniko Kentro Erevnas Kai Technologikis Anaptyxis, Thermi Thessaloniki, Greece
- Geniko Nosokomeio Papageorgiou, Thessaloniki, Greece
- Panepistimiako Geniko Nosokomeio Irakleiou, Irakleio, Greece
- Region Sormland, Nykoping, Sweden
- Technologiko Panepistimio Kyprou, Lemesos, Cyprus
- Universiteit Maastricht, Maastricht, Netherlands
- University Of Novi Sad, Faculty Of Medicine Novi Sad, Novi Sad, Serbia
- Univerzitet U Novom Sadu Fakultet Tehnickih Nauka, Novi Sad, Serbia
Small and medium-sized enterprises (SMEs) and mid-sized companies (<€500 m turnover)
- Agora Labs S.R.L., Collevecchio (Ri), Italy
- Ainigma Technologies, Leuven, Belgium
- European Dynamics Advanced Information Technology And Telecommunication Systems SA, Marousi Athina, GreeceThird-party
- Fwdfaster Ai Research BV, Utrecht, Netherlands
- Linac-Pet S.A. Opco Limited, Limassol, Cyprus
- Shine 2europe Lda, Coimbra, Portugal
- Timelex, Bruxelles / Brussel, Belgium
- Wellics LTD, London, United Kingdom
MedTech Europe
- Hict, Gent, BelgiumSME
Contributing partners
- Ethniko Kai Kapodistriako Panepistimio Athinon, Athina, Greece
- Idryma Technologias Kai Erevnas, Irakleio, Greece
Patient organisations
- Pagkyprios Syndesmos Karkinopathon Kai Filon 1986, Nicosia, Cyprus
Other companies
- European Dynamics Luxembourg SA, Luxembourg, Luxembourg
| Participants | |
|---|---|
| Name | EU funding in € |
| Agora Labs S.R.L. | 270 000 |
| Ainigma Technologies | 270 000 |
| Ancora Health BV | 3 200 000 |
| Aristotelio Panepistimio Thessalonikis | 220 000 |
| Centro Regionale Information E Communication Technology Scrl | 290 000 |
| Ethniko Kai Kapodistriako Panepistimio Athinon | 350 250 |
| Ethniko Kentro Erevnas Kai Technologikis Anaptyxis | 400 000 |
| European Dynamics Luxembourg SA | 400 000 |
| Fwdfaster Ai Research BV | 445 000 |
| Geniko Nosokomeio Papageorgiou | 140 000 |
| Hict | 627 078 |
| Idryma Technologias Kai Erevnas | 350 000 |
| Linac-Pet S.A. Opco Limited | 140 000 |
| Pagkyprios Syndesmos Karkinopathon Kai Filon 1986 | 140 000 |
| Panepistimiako Geniko Nosokomeio Irakleiou | 140 000 |
| Region Sormland | 140 000 |
| Shine 2europe Lda | 200 000 |
| Technologiko Panepistimio Kyprou | 210 000 |
| Timelex | 170 000 |
| Universiteit Maastricht | 240 000 |
| University Of Novi Sad, Faculty Of Medicine Novi Sad | 150 000 |
| Univerzitet U Novom Sadu Fakultet Tehnickih Nauka | 150 000 |
| Wellics LTD | 210 000 |
| Third parties | |
| Name | Funding in € |
| European Dynamics Advanced Information Technology And Telecommunication Systems SA | 90 000 |
| Total Cost | 8 942 328 |