Cenobamate is a new antiseizure medication used in recent years for adult drug-resistant focal epilepsy. Its pharmacological effects have two main features: on the one hand, it can regulate voltage-gated sodium channels, thereby reducing abnormal neuronal excitability; on the other hand, it can act as a positive allosteric modulator of γ-aminobutyric acid-A (GABA-A) receptors and enhance inhibitory neurotransmission. Several existing studies have shown that cenobamate can reduce the frequency of focal seizures and has certain advantages in improving seizure freedom rates. Its common adverse reactions are mainly central nervous system symptoms. At present, the clearest clinical position of cenobamate is still its use in adult drug-resistant focal epilepsy. Its application in children, generalized epilepsy, and special epilepsy syndromes still needs more evidence to support it. This article reviews the pharmacological mechanisms, pharmacokinetics, clinical efficacy, safety, and clinical position of cenobamate, with the aim of providing a reference for its standardized clinical use.
Epilepsy is a common chronic neurological disorder. Drug-resistant epilepsy (DRE) is defined as failure to achieve sustained seizure freedom after adequate trials of two appropriately chosen and tolerated anti-seizure medications (ASMs) regimens (as monotherapies or in combination). In this population, surgical resection and neuromodulation can effectively reduce seizure burden; however, their effectiveness is limited by uncertainty in epileptogenic zone localization, interindividual variability in stimulation targets and parameters, and procedure-related risks. As an emerging technology, brain–computer interface (BCI) offer a closed-loop framework of real-time monitoring, state decoding, decision-making, and intervention delivery, shifting therapy from fixed-parameter open-loop approaches to biomarker-driven, dynamically personalized modulation and providing new avenues for precision, individualized treatment of DRE. This review summarizes signal acquisition and decoding strategies for epilepsy BCI, closed-loop intervention paradigms, and key challenges in clinical translation.