High Throughput Behavioral Testing For Novel Antidepressants

描述（由申请人提供）：机密项目摘要/摘要本申请是根据NIMH精神障碍药理制剂和药物项目公告提交的。该提案的目标是通过结合最先进的自动行为分析技术和一种新的专门方法来发现治疗抑郁症的药物，来克服阻碍发现新的和改进的抗抑郁药物的主要障碍。尽管广泛使用和商业上的成功，目前的抗抑郁药有几个缺陷，包括疗效差和延迟起效。由于缺乏对这些药物的慢性影响敏感的可靠、高通量的行为分析，抗抑郁药物的发现进展严重滞后。我们建议开发SmartCube(r)， PsychoGenics的自动化，高通量行为测试系统，以筛选抗抑郁药的快速起效。在第一阶段，我们将开发一种筛选速效抗抑郁药的方法。为了实现这一目标，我们将首先在SmartCube(r)中建立慢性抗抑郁药特征的时间过程和开始作用。对于一小部分典型抗抑郁药（氟西汀、文拉法辛和丙咪嗪），慢性特征达到稳定状态所需的时间将被确定。这些抗抑郁药的慢性特征的开始将通过确定抗抑郁药特征更接近慢性而不是急性特征的最早时间来确定。然后，我们将利用这些信息在SmartCube(r)中建立一个慢性抗抑郁药特征的参考数据库。该参考数据库将用于筛选具有快速起效抗抑郁活性的新型化合物。多达100种先前在我们的急性抗抑郁药物SmartCube(r)筛选中显示出活性的化合物将进行快速起效活性测试。我们之前筛选的文库由已知的和新的、靶向特异性的、靶向非特异性的和靶向未确定的小分子组成。那些很有可能显示出慢性抗抑郁特征的化合物将被视为“初步成功”。这些化合物将在慢性抗抑郁药疗效测试中得到证实，该测试将测试作用的开始。在这些测试中至少有一项显示出快速起效活性的化合物将被视为“有效的成功”。在该提案的II期，将推进3-5个经过验证的靶点，并完成为第一先导物“优化先导物”提交IND所需的代谢、药代动力学和安全性研究。我们相信，这种方法将导致发现新的，更快的抗抑郁药。严重抑郁症代表了一个主要的未满足的医疗需求，但近年来引入市场的新药数量一直在稳步下降。传统的分子靶标驱动的抗抑郁药物发现方法由于复杂性和缺乏对该疾病分子基础的理解而取得了有限的成功。本提案中描述的基于行为的方法提供了一个令人兴奋的新选择，有可能更有效地识别新的、更有效的抗抑郁药，并且起效更快。

DESCRIPTION (provided by applicant): CONFIDENTIAL Project Summary/Abstract This application is being submitted in response to an NIMH program announcement for Pharmacological Agents and Drugs for Mental Disorders. The goal of the proposal is to overcome the major hurdles that have impeded the discovery of new and improved antidepressant medications by combining state of the art automated behavioral assay technology with a novel and specialized approach to the discovery of drugs for the treatment of depression. Despite wide use and commercial success, current antidepressants have several deficiencies including poor efficacy and delayed onset of action. Progress in antidepressant drug discovery has been delayed severely by the lack of reliable, high throughput behavioral assays sensitive to the chronic effects of these drugs. We propose to develop SmartCube(r), PsychoGenics' automated, high-throughput behavioral testing system, to screen antidepressants for rapid onset of activity. In Phase I, we will develop a methodology to screen for fast acting antidepressants. To accomplish this, we will first establish the time course and onset of action of the chronic antidepressant signature in SmartCube(r). The time required for the chronic signatures to reach a steady state will be determined for a small set of prototypical antidepressants (fluoxetine, venlafaxine and imipramine). The onset of the chronic signature will be determined for these antidepressants by establishing the earliest time at which the antidepressant signature more closely resembles the chronic rather than acute signature. We will then utilize this information to establish a reference database of chronic antidepressant signatures in SmartCube(r). This reference database will be used to screen novel compounds for fast onset antidepressant activity. Up to 100 compounds that have previously shown activity in our acute antidepressant SmartCube(r) screen will be tested for fast onset activity. The libraries that we have previously screened were comprised of a diverse mix of known and novel, target- specific, target-nonspecific and target-undetermined small molecules. Compounds that show a high probability of showing a chronic antidepressant signature will be considered "preliminary hits". These compounds will be confirmed in tests of chronic antidepressant efficacy that test for onset of action. Compounds that show rapid onset activity in at least one of these tests will be considered "validated hits". In Phase II of the proposal, 3-5 validated hits will be advanced and the metabolic, pharmacokinetic and safety studies required to file an IND for at lead one "optimized lead" will be completed. We believe that this approach will result in the discovery of novel, faster acting antidepressants. CONFIDENTIAL Project Narrative Major depression represents a major unmet medical need, but the number of new medications introduced to the market in recent years has been steadily declining. The traditional molecular target driven approached to drug discovery for antidepressants have had limited success due to the complexity and lack of understanding regarding the molecular basis of the disorder. The behavior-based approach described in this proposal provides an exciting new alternative with the potential to more efficiently identify novel, more efficacious antidepressants with a faster onset of action.