High throughput in vivo screening: translational generation of novel analgesics

描述（由申请人提供）：拟议研究的中心工作假设是直接体内高通量筛选（in vivo HTS）将产生增强的线索，从而加速发现具有更高安全性的镇痛药。这项工作延续了已完成的R21 （NIDA DA019620）题为“基于混合物的组合文库的体内筛选”的工作。本文描述的整体方法将加速药物发现和随后确定更先进的治疗候选者，准备进行临床前研究。小分子药物发现的传统方法是在选定的化合物进行体内测试之前，先通过体外HTS分析鉴定单个化合物。然而，这么晚才转向动物试验会导致高损耗率，这在时间和研究经费上都是昂贵的。为了规避这个问题，本建议采用一种新颖的翻译方法，能够在最早阶段消除无效化合物。这些研究的长期目标是在体内应用HTS来加速多个治疗领域的药物发现。作为实现这一目标的第一步，本申请中的具体目标是应用该技术来解决对有效但本质上更安全的镇痛化合物的需求。市场上销售的阿片类镇痛药既强效又有效，但极易上瘾，并有潜在的危及生命的副作用。该提案将确定有可能推进人体临床试验的新化学实体（NCEs），如果成功，将改善患者的生活质量，同时减少非医疗使用阿片类镇痛药带来的社会问题。这项提案的潜力显然支持NIDA的使命，即“领导国家将科学的力量用于药物滥用和成瘾”。该研究设计使用了一种筛选大型的、基于混合物的体内文库的方法，以鉴定在体内小鼠伤害感觉模型中有活性的化合物。共有37种可用的内部小分子文库混合物（代表超过700万个小分子）将在抗伤性动物模型中进行体内筛选，以确定用于开发的额外支架，补充先前确定的支架。从这三种支架中选择的单个化合物将被合成和纯化，用于进一步的开发，包括体外分析、药物分析和其他体内模型。最终，我们将研究多种支架，并选择2-3种新的化学实体进行临床前研究。在本研究结束时，我们将清楚地证明将基于大混合物的小分子文库与体内筛选（in vivo HTS）相结合的效用，以确定具有已证明的疗效和最小副作用的治疗靶点和先导。通过利用体内HTS，化合物可以通过先前未确定的生物学途径在体内发挥作用，从而在临床和科学领域提供潜在的进步。

DESCRIPTION (provided by applicant): The central working hypothesis of the proposed study is that the direct in vivo high throughput screening (in vivo HTS) will yield enhanced leads, thereby accelerating the discovery of analgesics with improved safety profiles. This work continues the work of the completed R21 (NIDA DA019620) entitled, "In Vivo Screening of Mixture-Based Combinatorial Libraries". The overall approach described herein will accelerate drug discovery and the subsequent identification of more advanced therapeutic candidates poised for preclinical studies. The traditional approach to small molecule drug discovery is to identify individual compounds through in vitro HTS assays, before selected compounds are tested in vivo. However, such a late transition to animal testing fosters a high rate of attrition that is costly in both time and research dollars. To circumvent this problem, this proposal utilizes a novel translational approach capable of eliminating non-efficacious compounds at the earliest stage. The long-term goal of these studies is to apply in vivo HTS to accelerate drug discovery in multiple therapeutic areas. As the first step towards that goal, the specific objective in the present application applies this technique to address the need for potent, but inherently safer, analgesic compounds. Marketed opioid analgesics are both potent and effective, but are strongly addictive with potentially life- threatening side effects. This proposal will identify new chemical entities (NCEs) with the potential to advance to human clinical trials and, if successful, improve patients' quality of life while reducing the societal problems posed by nonmedical use of opioid analgesics. The potential of this proposal is clearly supportive of the mission of NIDA, "to lead the Nation in bringing the power of science to bear on drug abuse and addiction." The research design uses a method of screening large, mixture-based libraries in vivo to identify compounds that are active in an in vivo mouse model of nociception. A total of 37 available, in-house, small molecule library mixtures (representing over 7 million small molecules) will be screened in vivo with animal models of antinociception to identify additional scaffolds for development, complementing a previously identified scaffold. Individual compounds selected from these three scaffolds will be synthesized and purified for additional development which will include in vitro analysis, pharmaceutical profiling, and additional in vivo models. Ultimately, we will examine multiple scaffolds and select 2-3 new chemical entities to initiate preclinical studies. By the end of the proposed study, we will have clearly demonstrated the utility of combining large mixture- based libraries of small molecules with in vivo screening (in vivo HTS) to identify therapeutic hits and leads with demonstrated efficacy and minimized side effects. By utilizing in vivo HTS, compounds may be identified with in vivo efficacies that function through previously unidentified biological pathways, providing potential advances in both the clinical and scientific realms.