When we think about the future of healthcare, it’s easy to imagine the impact of artificial intelligence — personalised treatment plans, early disease detection, clinical decision support. But behind all of that innovation lies one essential ingredient: Data.

At Trinity College Dublin (TCD), we’ve been asking a key question:

How can we enable cutting-edge research and AI innovation in healthcare — without compromising the privacy and trust of the people whose data powers it all?

That question led us to the SEARCH project, an IHI funded initiative exploring how synthetic data could transform the way health research and AI development are done.

The Promise of Synthetic Data

Synthetic data is exactly what it sounds like — data that’s artificially generated, but built to reflect the structure and patterns of real-world patient data. It can mimic the richness of clinical records, imaging, genomic data and more, without revealing any individual’s private information. In SEARCH, we’re part of a multidisciplinary team that includes hospitals, researchers and industry all working to create a federated network for AI in healthcare. That means data stays securely where it was generated, but researchers and AI models can still learn from it, through federated learning approaches.

TCD’s Role: Laying the Foundations for Reusable Synthetic Data

At TCD, we lead several parts of the project - but perhaps the most exciting part of our work is leading two real-world clinical case studies, which put synthetic data into action in meaningful ways. In short, these two thematic case studies will explore how synthetic data could support decision-making in areas of real-world clinical complexity — gynaecological cancers, including cervical cancer screening and ovarian cancer treatment planning. These case studies are being designed in close collaboration with public health and clinical research partners, and aim to demonstrate how synthetic datasets — once validated — could be used to model alternative care pathways, support triage strategies, and enhance predictive modelling in data-limited environments. While this work is still in its early phases, it reflects the practical potential of synthetic data to contribute to public health planning and personalised care — particularly in areas where privacy concerns or data scarcity have previously posed barriers.

Looking Ahead

These case studies reflect what makes SEARCH, and our work at TCD so exciting. We’re not just theorising about synthetic data; we’re showing how it can be applied in real-world healthcare settings to support smarter, safer, more effective decision-making. As the project progresses, we’ll continue to build the frameworks, datasets, and tools that enable federated AI innovation — while respecting the trust patients place in the healthcare system.

We look forward to sharing more along the way.

Trinity College Dublin SEARCH Team:

Aideen Long, Coordinator, SEARCH Project

Mr Frank Mangan, Business Development, Trinity Translational Medicines Institute

Professor John O’Leary, Chair of Pathology, Trinity College Dublin.

Dr Ola Ibrahim, Research Fellow, School of Medicine, Trinity College Dublin

Professor Cara Martin, School of Medicine, Trinity College Dublin

Professor Sharon O’Toole, School of Medicine, Trinity College Dublin

William McCormack PhD, Project Manager, Trinity College Dublin.