Epilepsy Benchmarks Area III: Improved Treatment Options for Controlling Seizures and Epilepsy-Related Conditions Without Side Effects. Issue 1 (January 2020)

• Record Type: Journal Article
• Authors: Traynelis, Stephen F.; Dlugos, Dennis; Henshall, David; Mefford, Heather C.; Rogawski, Michael A.; Staley, Kevin J.; Dacks, Penny A.; Whittemore, Vicky; Poduri, Annapurna
• Is Part Of: Epilepsy currents. Volume 20:Issue 1(2020)Supplement
• Page Start: 23S
• Page End: 30S
• Publication Date: 2020-01
• Subjects: NINDS benchmarks for epilepsy research -- Epilepsy Benchmarks -- progress in epilepsy research -- seizure mechanisms -- refractory epilepsy -- genetics -- real-time management of seizures -- epilepsy therapies; Epilepsy -- Periodicals; 616.853005
• DOI: 10.1177/1535759719895279
• Languages: English
• ISSNs: 1535-7597

Abstract

The goals of Epilepsy Benchmark Area III involve identifying areas that are ripe for progress in terms of controlling seizures and patient symptoms in light of the most recent advances in both basic and clinical research. These goals were developed with an emphasis on potential new therapeutic strategies that will reduce seizure burden and improve quality of life for patients with epilepsy. In particular, we continue to support the proposition that a better understanding of how seizures are initiated, propagated, and terminated in different forms of epilepsy is central to enabling new approaches to treatment, including pharmacological as well as surgical and device-oriented approaches. The stubbornly high rate of treatment-resistant epilepsy—one-third of patients—emphasizes the urgent need for new therapeutic strategies, including pharmacological, procedural, device linked, and genetic. The development of new approaches can be advanced by better animal models of seizure initiation that represent salient features of human epilepsy, as well as humanized models such as induced pluripotent stem cells and organoids. The rapid advances in genetic understanding of a subset of epilepsies provide a path to new and direct patient-relevant cellular and animal models, which could catalyze conceptualization of new treatments that may be broadly applicable across multiple forms of epilepsies beyond those arising from variation in a single gene. Remarkable advances in machine learning algorithms and miniaturization of devices and increases in computational power together provide an enhanced opportunity to detect and mitigate seizures in real time via devices that interrupt electrical activity directly or administer effective pharmaceuticals. Each of these potential areas for advance will be discussed in turn.