High throughput in vivo screening: translational generation of novel analgesics

描述(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(体内HTS)将产生增强的导联，从而加速发现安全性更好的止痛药。这项工作继续了完成的R21(NIDA DA019620)的工作，题为“基于混合物的组合库的体内筛选”。这里描述的总体方法将加速药物发现和随后确定更先进的治疗候选药物，为临床前研究做好准备。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，通过体外HTS检测来鉴定单个化合物。然而，如此晚地过渡到动物试验会导致高磨损率，这在时间和研究资金上都是昂贵的。为了绕过这个问题，这项建议使用了一种新的翻译方法，能够在最早阶段消除无效化合物。这些研究的长期目标是应用体内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，本申请中的特定目标应用这一技术来解决对有效但本质上更安全的止痛化合物的需求。市场上销售的阿片类止痛药既有效又有效，但具有很强的成瘾性，具有潜在的威胁生命的副作用。这项提案将确定有可能进入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剂带来的社会问题。这项提议的潜力显然支持了NIDA的使命，即“领导国家利用科学的力量来解决药物滥用和成瘾问题。”这项研究设计使用了一种在体内筛选大型、基于混合物的文库的方法，以识别在体内小鼠伤害性感受模型中活跃的化合物。总共37种可用的内部小分子库混合物(代表700多万个小分子)将通过抗伤害作用的动物模型在体内进行筛选，以确定更多用于开发的支架，以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，以进行进一步的开发，这将包括体外分析、药物分析和额外的体内模型。最终，我们将检查多个支架，并选择2-3个新的化学实体来启动临床前研究。到拟议的研究结束时，我们将清楚地展示将大的基于混合物的小分子文库与体内筛选(体内HTS)相结合的实用性，以识别具有已证明的有效性和最小副作用的治疗药物和先导药物。通过利用体内HTS，化合物可能被鉴定为具有体内有效性，这些化合物通过以前未知的生物途径发挥作用，在临床和科学领域提供了潜在的进展。

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.