This review examines drug-resistant epilepsy models, explores new therapies, and highlights innovative research directions.
Epilepsy is a long-term neurological disorder that results in recurring, uncontrolled seizures. These kinds of seizures are caused by excessively high and irregular electrical discharge in the central nervous system. Epilepsy is among the most common neurological disorders, with approximately 50–70 new cases/100,000 people every year. This review critically examines the current landscape of pharmacological experimental animal models employed in the study of drug-resistant and refractory epilepsy, shedding light on the complexities of this multifaceted disorder. Through an extensive analysis of preclinical models, the review explores the diverse mechanisms underlying resistance to antiepileptic drugs, emphasizing the need for innovative therapeutic strategies. This review was conducted using a comprehensive search of databases, including PubMed, Scopus, and Web of Science, focusing on studies published from 2000 to 2024. Articles were selected based on relevance to drug-resistant epilepsy (DRE) models, emerging technologies, and translational potential, using keywords such as DRE, animal models, and epileptogenesis. In addition, emerging experimental approaches, such as optogenetics, chemogenetics, and advanced imaging techniques, were scrutinized. Furthermore, this review outlines innovative approaches, including novel pharmacotherapies, gene therapies, and precision medicine interventions, that hold promise for overcoming drug resistance. By synthesizing current knowledge and identifying gaps, this article aims to guide future research directions and stimulate innovative strategies for developing effective interventions for drug-resistant and refractory epilepsy. Ultimately, a comprehensive grasp of experimental models and innovative approaches is crucial for advancing our understanding of epilepsy pathophysiology and paving the way for more efficacious and personalized therapeutic interventions.
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Shrivastava et al. (2025) studied this question.
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