ROYAL COLLEGE OF SURGEONS IN IRELAND

In response to the growing need for specialized data scientists in healthcare, our initiative aims to establish an international, interdisciplinary graduate school that educate the next generation of medical data scientists, with a strong translational focus bridging academia and industry. This is strengthened by the active involvement of leading global pharmaceutical and med-tech companies as well as SMEs in the AI field, thus ensuring that our research and training remain at the forefront of industry and healthcare. We propose a comprehensive training program offering PhD students not only a robust foundation in data science, including AI/ML and digital health, but also a deep understanding of ethical, legal and regulatory frameworks, including GDPR, the European Health Data Space and the AI Act. Our curriculum is unique in its integration of entrepreneurial thinking and a focus on Parkinson’s disease (PD) as an application field. At the same time, the methodologies and insights gained will have broader applications in various disorders, thus applicable to other areas of healthcare. We will move with our research program clearly beyond the state of the art by: - Developing new AI/ML models spanning the entire journey of a PD patient to support medical decision-making on a more individual basis, - Pioneering the use of recent causal AI/ML techniques in PD research, - Investigating the optimization of future clinical trials, - Providing novel insights into digital and neuroimaging markers, - Developing innovative algorithmic solutions to enhance the generalizability of AI/ML models, - Providing understanding of the ethical, legal and regulatory basis of the use of AI in medical practice. All participants are highly committed to the research, teaching, supervision and management activities in this program, and this commitment is supported by existing working relationships through other projects, such as ERA PerMed DIGIPD, IHI PREDICTOM and IHI IDERHA.

EC contribution:

EUR 573k

Start:

2024-11-01

End:

2028-10-31

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-DN-ID

Call:

HORIZON-MSCA-2023-DN-01

View on CORDIS (DOI 10.3030/101168379)

Immunotherapies promise to be the major break-through in the treatment of metastatic cancer, but effectiveness is limited to few cancer types. Metastatic neuroblastoma, breast and prostate cancer, affecting approximately 300,000 EU-27 inhabitants of all age groups in 2020, respond not or very poorly to current immunotherapies. To establish more effective immunotherapies, we need to better understand the specific tumour cell-immune host interactions at the metastatic site. The Mac4Me Doctoral Network adopts an innovative, multidisciplinary and cross-sectional approach, with a unique and dedicated research training programme to equip young researchers with scientific knowledge and transferable skills that are essential for today’s great demand in both academic and non-academic sectors. Mac4Me aims to understand the tumour cell-immune host interactions at the metastatic site. with an in-depth molecular and mechanistic understanding of the immune and matrix changes induced by tumour cells. We will use innovative animal-free organ-on-chip systems, that recapitulate early metastasis formation of brain, bone and liver. The retrieved knowledge from the preclinical models will be integrated in data from established clinical metastases and AI machine learning algorithms will be applied to identify new immune targets. Mac4Me will align with patients and the general public from the very beginning thereby bringing societal expectations and patient needs into the centre of the project to pave the way for new standards for shared decision making and acceptable health care solutions. Mac4Me will prepare a next generation of young scientists to start their own career as independent researchers being equipped with scientific knowledge and personal skills and integrating participatory science as a starting point to address the societal demand for more effective treatment solutions for incurable metastatic disease, such as neuroblastoma, breast and prostate cancer.

EC contribution:

EUR 573k

Start:

2024-11-01

End:

2028-10-31

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-DN

Call:

HORIZON-MSCA-2023-DN-01

View on CORDIS (DOI 10.3030/101168661)

Schizophrenia affects a staggering 21 million people worldwide, with 80% of these citizens suffering from a relapsing disease, putting their health and safety at enormous risk. Timely detection of these psychotic relapses would require very frequent contact with clinicians, which is neither desirable nor feasible. An accurate online relapse predictor could alert clinicians of subtle deterioration, which enables timely intervention and allow safe discontinuation of long-term medication, which so many affected citizens desire. Our Consortium demonstrated that subtle alterations in speech carry a predictive signal for psychosis onset. This project will develop an AI monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate the relapse risk. The monitoring tool we develop will be validated retrospectively in a longitudinal cohort, cross-sectionally, across six languages, after which it will be tested prospectively in a multicenter randomized trial, with the end goal of improving functional and clinical outcomes of those affected by schizophrenia. Developing such a system for exceptionally vulnerable people requires ‘buy-in’ from clinicians and mental health care service users, namely trust. A lack of trust is the biggest obstacle to the real-world implementation of a speech-based monitoring system. TRUSTING will develop a framework that systematically ensures addressing all the criteria for trustworthy AI put forward by the EU. This will ensure an empirically based and validated tool that can reliably detect pending relapse. As the core philosophy of trustworthiness is part of every aspect of the project, it will be a system more likely to be welcomed and embraced by service users and their carers. TRUSTING generates the scientific and social foundation for disruptive technology to deliver the unmet promise of an equitable and just form of healthcare for people at risk of relapse.

EC contribution:

EUR 508k

Start:

2023-07-01

End:

2028-12-31

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-HLTH-2022-STAYHLTH-01-two-stage

View on CORDIS (DOI 10.3030/101080251)

WiseFood aims at developing smart digital applications that will empower citizens to make healthier and more sustainable food choices. It will leverage state-of-the-art Artificial Intelligence (AI) techniques and tools, combining the factual knowledge representation capacity of Knowledge Graphs with the natural language understanding, generation, and reasoning abilities of Large Language Models. These will allow us to build novel tools that democratize access to reliable food-related information and go beyond the current levels of personalization and contextualization offered by existing food recommenders. The developed applications will be user-friendly and integrate seamlessly into daily life, not requiring specialized IT skills or devices. Our goal is to bridge the divide between knowledge, intention, and action with end-to-end intelligent solutions. A human-in-the-loop approach with food domain experts, including nutritionists, will be applied to ensure alignment with national policies and guidelines. Living Labs implementing a multi-actor approach are foreseen to co-create the envisioned solutions. These will take place in three different countries, Ireland, Hungary, and Slovenia, with the latter being an already established and operational short food supply chain Living Lab. The outcomes of WiseFood will enhance the overall food ecosystem, by promoting healthier dietary habits, reducing the ecological footprint of food consumption, and fostering a culture of well-informed and eco-conscious citizens.

EC contribution:

EUR 459k

Start:

2025-01-01

End:

2027-12-31

Status:

SIGNED

Scheme:

HORIZON-IA

Call:

HORIZON-CL6-2024-FARM2FORK-01

View on CORDIS (DOI 10.3030/101181895)

Bone atrophy and fractures, resulting from trauma, infections, osteoporosis, or cancer, are global health concerns. Standard care with cement and bone grafts has limitations. Synthetic polymers like polymethyl methacrylate risk leakage, spinal issues, and poor healing. Donor shortages for allogenic bone grafting and invasive procedures pose risks such as rejection and viral transmission. HYDROHEAL innovates with hydrogel formulations to address bone strength challenges by treating vertebral and alveolar fractures. HYDROHEAL aims to develop safe, sustainable scaling, and cost-effective formulations using renewable biomaterials for targeted drug delivery, aligning closely with the EU Circular Economy Action Plan and Chemicals Strategy for Sustainability. It is ready to introduce a new era in fracture therapy. The proposed self-solidifying hydrogels release active pharmaceutical ingredients locally upon external stimulation, potentially improving treatment efficacy, preventing infections, and speeding up fracture healing. The objectives of the project are: 1. Develop novel injectable hydrogel formulations combining natural substance derivates to enhance healing, inhibit bacterial growth, and monitor therapy progress in vivo. 2. Simultaneously manufacture carriers as micro- and nano-particles, surface-functionalized to incorporate pharmaceutical agents, releaseable upon external stimuli for tailored drug release. 3. Validate safe and optimized hydrogel formulations for treating vertebral and alveolar bone fractures through in vitro and in vivo tests. 4. Demonstrate scalable and sustainable biomaterial manufacturing through safe design methods, machine learning, and predictive life cycle assessment. 5. Develop machine learning and hybrid digital modeling methods, combining adaptive design of experiments and physics-based modeling with advanced characterization techniques.

EC contribution:

EUR 416k

Start:

2025-06-01

End:

2029-05-31

Status:

SIGNED

Scheme:

HORIZON-IA

Call:

HORIZON-CL4-2024-RESILIENCE-01-TWO-STAGE

View on CORDIS (DOI 10.3030/101178398)

Up to one fifth of young people report that they have experienced unusual perceptual experiences, thoughts or beliefs. These experiences (which we call Psychotic Experiences or PE) can take the form of hearing voices or seeing visions or feeling paranoid or believing things that are not true. As part of my ERC Consolidator Award (iHEAR), I and my team have learned a great deal more about these experiences and what they mean for young people. We know that these experiences can be transitory in most cases but that in some young people they recur throughout adolescence and adulthood. We know that, for some young people, these experiences can be associated with poor functioning and poorer mental health but for others they are not pathological. We have identified the need for an instrument that can differentiate between pathological and non-pathological psychotic experiences. This will support early risk screening and development of interventions among those who experience PE. We propose to search for natural language patterns within self-reported PE that are associated with high and low levels of mental ill-health. Our hypothesis is that young people’s first person account of their experiences are likely to contain natural language phrases that could be used to differentiate between PEs that occur in the context of mental ill-health are likely to require intervention and those that do not. Knowledge of natural language patterns for PE would be a valuable step in improving assessment tools in clinical practice. Additionally this could be a valuable new resource for digital tools and e-Health which is a growing area for mental health.

EC contribution:

EUR 44k

Start:

2024-01-01

End:

2026-12-31

Status:

SIGNED

Scheme:

HORIZON-ERC-POC

Call:

ERC-2022-POC2

View on CORDIS (DOI 10.3030/101100943)