Löscher Wolfgang
Prevention of epilepsy in patients at risk is an urgent global unmet need. In theory, the latent period between an epileptogenic brain insult and the onset of epilepsy may offer a therapeutic window to interfere with epileptogenesis. Numerous preclinical and a few clinical studies on antiepileptogenesis have been performed in the past 20-plus years. The vast majority of these studies used treatments with single, often highly selective drugs shortly after epileptogenic brain injuries, mostly without any success. The negative results may be due to the complex mechanisms of epileptogenesis, which complicate any strategy to interfere with this process. It was therefore proposed to apply principles of network pharmacology to the search for antiepileptogenic treatments. Here the outcome of preclinical studies using rationally chosen drug combinations for antiepileptogenesis is reviewed. Of 24 drug combinations that are discussed here, only four exerted persistent antiepileptogenic efficacy in rodent models of acquired epilepsy. For three of these effective combinations, clinically approved drugs were used, which would facilitate translation into clinical trials. The chapter also discusses future advancements in the search for antiepileptogenic drugs or drug combinations, including the subsequent use of in silico, in vitro, and in vivo platforms as well as “big data” mining approaches and machine learning.
预防癫痫高危患者的癫痫发作是全球亟待满足的迫切需求。理论上,致痫性脑损伤与癫痫发作之间的潜伏期可能提供一个干预癫痫发生的治疗窗口。在过去20多年里,已经开展了大量关于抗癫痫发生的临床前研究和一些临床研究。这些研究绝大多数在致痫性脑损伤后不久使用单一的、通常是高度选择性的药物进行治疗,但大多未取得成功。负面结果可能归因于癫痫发生机制的复杂性,这使得任何干预该过程的策略都变得复杂。因此,有人提出将网络药理学原理应用于寻找抗癫痫发生的治疗方法。本文综述了使用合理选择的药物组合进行抗癫痫发生的临床前研究结果。本文讨论的24种药物组合中,只有4种在获得性癫痫的啮齿动物模型中发挥了持续的抗癫痫发生疗效。对于其中3种有效的组合,使用了临床批准的药物,这将有助于转化为临床试验。本章还讨论了在寻找抗癫痫发生药物或药物组合方面未来的进展,包括随后使用计算机模拟、体外和体内平台以及“大数据”挖掘方法和机器学习。