Predictive Smoking Cessation Preclinical Battery

预测性戒烟临床前电池

基本信息

批准号：
8901369
负责人：
Taleen G Hanania
金额：
$ 69.11万
依托单位：
PSYCHOGENICS, INC.
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-30 至 2016-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8901369
关键词：
Academia Action Potentials Acute Affective Agonist Algorithms Animals Anti-Anxiety Agents Antidepressive Agents Antismoking Anxiety Area Behavioral Bioinformatics Bupropion Chronic Clinic Clinical Clonidine Cognition Cognitive Collaborations Conditioned Stimulus Cytosine Data Base Management Data Set Databases Decision Theory Development Discipline Discrimination Drug Addiction Drug abuse Economics Emotional Ensure Exhibits FDA approved Fluoxetine Future GABA Agonists Goals Gold Government Health Care Costs Impaired cognition Impulsivity Industry Knowledge Ligands Machine Learning Marketing Mecamylamine Mental Depression Methods Moclobemide Naloxone Neurobiology Nicotine Nicotine Dependence Nicotine Withdrawal Nicotinic Agonists Nortriptyline Output Pattern Pharmaceutical Preparations Phase Pre-Clinical Model Preclinical Drug Evaluation Preclinical Testing Property Relapse Research Rewards Science Series Smoker Social Welfare Stimulus Stress Testing Therapeutic Training Ursidae Family Withdrawal addiction base behavior test clinical efficacy combat computerized tools cost drug development drug discovery efficacy testing improved innovation interest member nicotine abuse novel pre-clinical programs public-private partnership receptor research and development screening smoking cessation success tool trait varenicline

项目摘要

DESCRIPTION (provided by applicant): Despite great advances in both the understanding of the neurobiology of addiction and the development and approval of smoking cessation therapies, a significant need remains for better smoking cessation aids. Our goal is aligned with NIDA's intent to bring the power of science to bear on drug abuse and addiction. We propose to use tools from a broad range of disciplines, and promise rapid and effective dissemination and use of the results of the proposed research to significantly improve treatment of nicotine abuse and addiction. The platform we propose to use will help identify, evaluate, and develop innovative medications to treat nicotine abuse and addiction. We propose to implement a research program through collaborations with academia, industry and government. Although there are two first-line (varenicline and bupropion) and two second-line (clonidine and notriptyline) approved medications for smoking cessation that significantly help to stop smoking, about 80% of smokers are unable to remain abstinent. As an explanation for such low success rate, it has been hypothesized that addiction develops in the presence of predisposing cognitive and affective states, which are unaffected by existing therapeutics but could be targeted by new smoking cessation aids for improved efficacy. One of the main reasons for the slow development of novel medications with improved efficacy is the lack of clearly translatable preclinical models of nicotine dependence that exhibit high degrees of predictive validity. Most preclinical tests are simply based on blocking nicotine-like effects but ignore other predisposing or underlying factors, either cognitive or emotional, that may trigger and maintain nicotine abuse. The availability of both approved medications and failed compounds gives us the opportunity to create a battery of nicotine dependence and CNS efficacy tests with enhanced predictive validity, potentially a key tool in enhancing future discovery and development efforts. During Phase I we will develop a test battery based on 1) consideration of multiple aspects underlying abuse (rewarding effects of acute and chronic nicotine, alleviation of withdrawal, relapse, anxiety, depression, cognitive dysfunction and impulsivity), 2) definition of a smoking cessation predictive score through a machine learning algorithm trained on a behavioral dataset generated with both effective and ineffective medications in our test battery and 3) minimization of animal and throughput costs. During Phase II the platform will grow to comprise a database of compounds and mechanisms of action of postulated smoking cessation potential, prioritized by their smoking cessation scores and predicted superiority in combating emotional and cognitive aspects of nicotine dependence. Finally, this platform (battery, database and computational tools) will be offered during Phase III as drug screening method to the members of a private public partnership, created to maintain, support, further develop and publicize the platform. The novelty of this project resides in the combination of economic principles and bioinformatics methods to take advantage of existing smoking cessation FDA-approved gold standards, the inclusion of cognitive and emotional state-relevant testing in the proposed preclinical battery, the creation of a knowledge database, and the management of the final platform by a private-public consortium to ensure maximal quality, value and access. We expect that the knowledge and tools generate by this project will stimulate further research and drug development both for smoking cessation and across other areas of drug abuse and discovery.

描述（由申请人提供）：尽管在成瘾神经生物学的理解以及戒烟疗法的开发和批准方面都取得了巨大进步，但仍然非常需要更好的戒烟辅助工具。我们的目标与 NIDA 的意图一致，即利用科学的力量来解决药物滥用和成瘾问题。我们建议使用广泛学科的工具，并承诺快速有效地传播和使用拟议研究的结果，以显着改善尼古丁滥用和成瘾的治疗。我们建议使用的平台将有助于识别、评估和开发治疗尼古丁滥用和成瘾的创新药物。我们建议通过与学术界、工业界和政府合作实施一项研究计划。尽管有两种一线（伐尼克兰和安非他酮）和两种二线（可乐定和诺替林）批准的戒烟药物可显着帮助戒烟，但约 80% 的吸烟者无法保持戒烟。作为成功率如此低的解释，有人假设成瘾是在易感认知和情感状态存在的情况下形成的，这些状态不受现有疗法的影响，但可以通过新的戒烟辅助手段来提高疗效。疗效提高的新型药物开发缓慢的主要原因之一是缺乏具有高度预测有效性的明确可转化的尼古丁依赖临床前模型。大多数临床前测试只是基于阻断尼古丁样作用，但忽略了可能引发和维持尼古丁滥用的其他诱发因素或潜在因素，无论是认知因素还是情感因素。已批准药物和失败化合物的可用性使我们有机会创建一系列具有增强预测有效性的尼古丁依赖和中枢神经系统功效测试，这可能是加强未来发现和开发工作的关键工具。在第一阶段，我们将基于 1) 考虑滥用背后的多个方面（急性和慢性尼古丁的奖励作用、戒断症状的缓解、复发、焦虑、抑郁、认知功能障碍和冲动），2) 吸烟的定义来开发一组测试。通过机器学习算法训练戒烟预测分数，该算法在我们的测试电池中使用有效和无效药物生成的行为数据集上进行训练，以及 3）最小化动物和吞吐量成本。在第二阶段，该平台将发展成为一个包含假定戒烟潜力的化合物和作用机制的数据库，按其戒烟分数和预测在对抗尼古丁依赖的情感和认知方面的优势进行优先排序。最后，该平台（电池、数据库和计算工具）将在第三阶段作为药物筛选方法提供给私人公共合作伙伴关系的成员，该合作伙伴关系的创建是为了维护、支持、进一步开发和宣传该平台。该项目的新颖性在于结合了经济原理和生物信息学方法，以利用 FDA 批准的现有戒烟黄金标准，在拟议的临床前电池中纳入认知和情绪状态相关测试，创建知识数据库，并由公私联盟管理最终平台，以确保最大的质量、价值和访问。我们期望该项目产生的知识和工具将刺激戒烟以及药物滥用和发现的其他领域的进一步研究和药物开发。