Moderate-throughput screening for anti-epileptogenic drugs.

描述（由申请人提供）：筛选预防脑损伤后癫痫的药物一直非常困难，因为自发性复发性癫痫发作开始是逐渐开始的，并且癫痫发作之间的间隔变化很大，因此需要长期、密集的癫痫发作监测来确定药物是否预防癫痫。一个严格而快速的筛选将使我们能够测试许多有前途的化合物的抗癫痫特性，并将为癫痫研究人员提供一个急需的测定，以测试他们的实验室开发的新化合物。我们开发了一套新的技术，可以大规模筛选抗癫痫药物。在与哈佛医学工程中心的合作中，我们开发了一种由玻璃芯片组成的癫痫发生体外模型，该模型可用于培养、记录和给药，每个芯片有32个器官型脑切片。我们最近发现，这些脑切片培养物经历了一个快速的、可预测的癫痫发生过程，而且器官型脑切片对抗惊厥药物的反应就像人类患者一样。我们最近发表了连续记录和量化电图尖峰和癫痫发作的计算机算法，并与国家神经疾病和中风研究所（NINDS）抗惊厥药物筛选计划的研究员艾德·杜德克（Ed Dudek）合作，我们在两种癫痫发生的体内模型和体外模型中验证了这些算法。我们将使用我们新创建的技术对药物库进行大规模并行筛选，以预防，减少或逆转癫痫发生。其中一个库是NINDS定制化合物库;我们将重点关注已经获得FDA批准的561种化合物。我们建议对这些化合物进行快速、严格的两阶段筛选，以确定其抗癫痫特性。在第一阶段，我们将使用平行培养的脑切片测定来筛选化合物。然后，预防、减少或逆转癫痫发生的化合物将进入第二阶段，其中最有希望的化合物将进行更严格但慢得多的第二次测定，即癫痫发生的红藻氨酸模型。在这两个阶段，将使用连续记录和分析的EEG数据定量测定电描记癫痫发作活动。这项研究将导致U 01。R21资助的筛选项目的结果可能会产生具有足够活性的化合物，以开始临床试验。或者，R21将提供先导化合物，使我们能够申请NINDS神经系统疾病和障碍新药蓝图大挑战，这样我们就可以筛选更大的化合物库，并与哈佛神经发现中心神经变性药物发现实验室（LDDN）的药物化学家合作优化化合物。 公共卫生相关性：由于癫痫发作开始非常缓慢，且发作间隔时间差异很大，因此需要长期、密集的癫痫发作监测来确定药物是否能预防癫痫，因此一直无法筛选出预防脑损伤后癫痫发作的药物。我们已经开发了一套技术，使大规模筛选策略的应用，这个问题。自发性癫痫的培养脑切片将被部署在一个高度平行的筛选程序中，作为筛选的第一阶段。体内试验将用于确认在第一阶段筛选中发现的最有希望的药物的效果。

DESCRIPTION (provided by applicant): It has been extremely difficult to screen for drugs that prevent epilepsy after brain injury, because spontaneous recurrent seizures begin gradually and the interval between seizures varies widely, so that long-term, intensive seizure monitoring is required to determine whether a drug prevents epilepsy. A rigorous yet rapid screen would enable us to test many promising compounds for anti-epileptogenic properties, and would provide epilepsy researchers with a much-needed assay to test new compounds developed within their laboratories. We have developed a new set of technologies to enable large-scale screening for antiepileptic drugs. In collaboration with the Harvard Center for Engineering in Medicine, we have developed an in vitro model of epileptogenesis comprised of glass chips that can be used to culture, record from, and administer drugs to arrays of 32 organotypic brain slices per chip. We have recently shown that these brain slice cultures undergo a rapid, predictable process of epileptogenesis, and that the organotypic brain slices respond to anticonvulsant drugs just as human patients do. We have recently published computer algorithms for continuously recording and quantifying electrographic spikes and seizures, and in collaboration with Ed Dudek, an investigator in the National Institute of Neurological Diseases and Stroke (NINDS) Anticonvulsant Screening Program, we have validated these algorithms in two in vivo models of epileptogenesis as well as in the in vitro model. We will use our newly-created technologies to execute large-scale, parallel screening of drug libraries for agents that prevent, reduce, or reverse epileptogenesis. One such library is the NINDS Custom Compounds library; we will focus on the 561 compounds that have already been approved by the FDA. We propose to subject these compounds to a rapid, rigorous two stage screen for anti-epileptogenic properties. In the first stage, we will screen compounds using parallel cultured brain slice assays. Compounds that prevent, reduce, or reverse epileptogenesis will then progress to the second stage, in which the most promising compounds will be subjected to a more rigorous albeit much slower second assay, the kainate model of epileptogenesis. In both stages, electrographic seizure activity will be assayed quantitatively using continuously recorded and analyzed EEG data. This research will lead to a U01. The results of the R21-funded screening project may produce compounds that are sufficiently active to begin clinical testing. Alternatively, the R21 will provide lead compounds that will enable us to apply for the NINDS Blueprint Grand Challenge for New Drugs for Diseases and Disorders of the Nervous System, so that we can screen larger compound libraries and optimize compounds in collaboration with the medicinal chemists at The Laboratory for Drug Discovery in Neurodegeneration (LDDN) in the Harvard NeuroDiscovery Center. PUBLIC HEALTH RELEVANCE: It has not been possible to screen for drugs that prevent epilepsy after brain injury, because seizures begin to occur very gradually, and the interval between seizures varies widely, so that long-term, intensive seizure monitoring is required to determine whether a drug prevents epilepsy. We have developed a set of technologies that makes possible the application of large-scale screening strategies to this problem. Cultured brain slices that become spontaneously epileptic will be deployed in a highly parallel screening program as a first stage in screening. In vivo testing will be used to confirm the effects of the most promising agents found in the first stage of screening.