Rao, Vikram R.

Abstract Seizure forecasting has progressed from theoretical aspiration to a rapidly advancing research domain, yet clinical translation remains limited. Over the past decades, advances in algorithm development, chronic electroencephalography (EEG), wearable sensors, and the characterization of seizure cycles have demonstrated that seizure risk is not random but fluctuates according to identifiable biological rhythms and patient‐specific patterns. Forecasting algorithms have shown promising performance across diverse retrospective datasets, including intracranial EEG, subscalp recordings, wearable physiological signals, and even self‐reported diaries. However, the clinical value of forecasting is contentious. Prospective real‐world validation and regulatory approval of patient‐facing forecasting systems remain rare. This review incorporates perspectives presented at the 5th International Congress on Mobile Health and Digital Technology in Epilepsy (2025). We examine barriers impeding clinical translation and current attempts to address them. Crucially, forecasting performance cannot be evaluated in isolation from intended use. Applications range from low‐risk uses, like scheduling diagnostic monitoring or visualization of historical trends, to higher risk interventions, including medication titration and adaptive neuromodulation. Each application entails distinct performance thresholds, ethical considerations, and regulatory requirements. Translational challenges include reliable seizure annotation, nonstationarity dynamics of biological cycles, and practical constraints for real‐time deployment. Ethical concerns center on miscalibrated reliance on low‐risk states, potential anxiety associated with high‐risk advisories, and the heterogeneity of patient preferences and risk tolerance. Regulatory pathways are likely to depend on clearly defined use cases and clinically meaningful endpoints, which may extend beyond seizure counts to include quality of life, anxiety, locus of control, and other patient‐reported outcomes. Ultimately, translation will require rigorous prospective evaluation against transparent benchmarks, sustainable scientific–commercial partnerships, and integration of probabilistic risk information into clinical workflows. With careful implementation, seizure forecasting may evolve from proof‐of‐concept research into a clinically meaningful component of epilepsy management, and we remain cautiously optimistic.

Abstract Neuromodulation is approved for the treatment of drug‐resistant epilepsy. It has been increasingly utilized over the past two decades with the approval of deep brain stimulation (DBS) and responsive neurostimulation (RNS) in addition to vagus nerve stimulation (VNS)—particularly in patients who are not deemed to be good resective surgical candidates or in case of patient preference. In this seminar in epileptology article, we address learning objective 3.7 “Demonstrate knowledge of indications, limitations and risks for vagal nerve stimulation and other neuromodulation techniques” of the International League Against Epilepsy curriculum for epileptologists. We will review the indications for neuromodulation, device programming, surgical considerations for implantation, side effects, effects on sleep, and mood. This is complemented by case examples that provide perspective for trainees, along with an outlook on future directions for neuromodulation in epilepsy. This article aims to serve as a learning resource for trainees in neurology, clinical neurophysiology, and epileptology by providing guidance in how to navigate the landscape of neuromodulation in epilepsy.