The International League Against Epilepsy (ILAE) is embarking on a transformative initiative to advance epilepsy research through large-scale, accessible datasets. This effort, led by the ‘Big Data’ Commission of the ILAE, aims to consolidate and connect diverse and siloed data from clinical records, EEG, imaging, and genomics into large, comprehensive datasets for research use. The goal: to drive new insights and inform novel treatment strategies for epilepsy, making data science in epilepsy more inclusive and impactful on a global scale. 

Professor Gianpiero Cavalleri, Deputy Director of the FutureNeuro Research Ireland Centre, and Professor of Human Genetics at RCSI, said: “Epilepsy is an incredibly diverse neurological condition, of which there are likely many more forms and subtypes than we currently appreciate. This effort by the ILAE is an early step towards connecting different epilepsy-related datasets, to enable more powerful analysis, allowing scientists better understand the different forms of epilepsy and how best to treat them” 

Why Big Data for Epilepsy? 

Analysis of ‘big data’ for the epilepsies holds the potential to uncover patterns and insights that traditional analysis of local (siloed) datasets miss. While many studies often focus on specific epilepsy syndromes or limited demographics, big data allows for a more comprehensive and better powered analysis that can capture and help understand the vast diversity within epilepsy cases. This means understanding not only seizure patterns but also co-existing conditions, responses to treatment, and long-term outcomes across diverse patient populations. 

Building Accessible and Inclusive Datasets 

One of the key goals of the ILAE Big Data Commission is to ensure epilepsy-related datasets are accessible to researchers worldwide. By addressing challenges in data standardisation, interoperability, and privacy, the Commission has established a framework for ethically managed datasets that are accessible around the world. The focus on inclusivity aims to make epilepsy data science beneficial not only for high-resource settings but also for researchers and patients in low-resource regions, where access to epilepsy care is often limited. 

AI and Machine Learning for Deeper Insights 

Artificial intelligence (AI) and machine learning have emerged as important tools for analysing large epilepsy datasets. These technologies help researchers identify intricate patterns and predict outcomes with greater precision than ever before. Machine learning applications within big data promise advances in real-time monitoring and personalised treatment planning, enhancing patient care and offering a more tailored approach to managing epilepsy. By applying AI to large datasets, researchers may discover previously unknown factors influencing seizure activity or new biomarkers that could enable earlier and more accurate diagnoses. 

The Importance of Community Engagement 

The ILAE Big Data Commission emphasises that big data research is all about collective and inclusive action, engaging not just data scientists but also clinicians, researchers, policymakers, and, most importantly, people affected by epilepsy. Their lived experiences play a critical role in shaping research priorities, defining person-centred outcomes, and improving the ethics and dissemination of studies. From contributing to clinical guidelines to guiding the use of AI in decision-making, their perspectives ensure research addresses real-world needs. This collaborative approach reflects FutureNeuro’s mission to bridge research and clinical practice for meaningful, patient-centred outcomes. 

Towards a New Era in Epilepsy Research 

As we enter this new era, big data and shared efforts are set to reshape the landscape of epilepsy care, bringing us closer to more personalised and effective treatments for people living with epilepsy around the world.