A phenotypic screen for osteoarthritic pain therapeutics using all-optical electrophysiology.

项目摘要：使用全基因组技术进行骨关节炎疼痛治疗的表型筛选- 光电生理学 慢性疼痛影响着美国超过1亿的成年人，其中许多人无法找到 缓解目前的药物。在这些患者中，近1/3患有骨关节炎。 目前慢性疼痛的治疗方法包括阿片类药物和非甾体类炎症剂。 然而，这些药物在慢性治疗中的功效受到药物开发的限制。 耐受性和剂量限制性毒性。特别是阿片类药物具有高度成瘾性和依赖性 造成了巨大的社会负担。尽管有明确的、未满足的医疗需求和重大的 研究活动，很少有新的类别的非阿片类药物靶向慢性疼痛出现， 过去十年 Quell Therapeutics使用Optopatch平台进行全光学电生理学 以足以进行表型筛选的通量在神经元中进行测量。使用工程化 光遗传蛋白，蓝光和红光可用于刺激和记录神经元活动， 分别定制显微镜可记录100个个体的电生理学 并行神经元具有高灵敏度和时间分辨率，这是目前还没有的能力。 可与任何其他平台筛选技术配合使用。 在这里，我们将Optopatch平台与慢性疼痛的体外模型相结合， 根神经节（DRG）感觉神经元沐浴在炎症介质的混合物中， 在骨关节炎患者的关节中。用炎症混合物处理的神经元 变得过度兴奋，模仿预期的细胞疼痛反应。我们计算 关节炎疼痛的功能表型，其捕获动作电位形状的差异 和对不同刺激的反应率。我们将筛选小分子化合物， 逆转疼痛表型，同时最小化与疼痛表型正交的神经元行为的扰动。 疼痛表型，体外“副作用”。我们将反筛选来自 大脑皮层和心肌细胞从心脏优先考虑化合物，选择性地发挥作用， 发炎的感觉神经元排名最高的化合物将进行化学优化， 将表征它们的药代动力学、药物代谢和体内功效。我们的目标是 推进疼痛的治疗发现，这可能最终有助于缓解美国阿片类药物危机。

Project Summary: A phenotypic screen for osteoarthritic pain therapeutics using all- optical electrophysiology Chronic pain affects over 100 million adults in the United States, many of whom cannot find relief with current medications. Of these patients, nearly 1/3 of them suffer from osteoarthritis. Current treatments for chronic pain include opioids and non-steroidal inflammatory agents. However, efficacy of these drugs in chronic treatment is restricted by the development of tolerance and dose-limiting toxicities. Opioids in particular are highly addictive, and dependency has caused a large societal burden. Despite the clear, unmet medical need and significant research activity, few new classes of non-opioid drugs targeting chronic pain have appeared in the past decade. Quell Therapeutics uses the Optopatch platform for making all-optical electrophysiology measurements in neurons at a throughput sufficient for phenotypic screening. Using engineered optogenetic proteins, blue and red light can be used to stimulate and record neuronal activity, respectively. Custom microscopes enable electrophysiology recordings from 100’s of individual neurons in parallel with high sensitivity and temporal resolution, a capability currently not available with any other platform screening technology. Here, we combine the Optopatch platform with an in vitro model of chronic pain, where dorsal root ganglion (DRG) sensory neurons are bathed in a mixture of inflammatory mediators found in the joints of osteoarthritis patients. The neurons treated with the inflammatory mixture become hyperexcitable, mimicking the anticipated cellular pain response. We calculate the functional phenotype of arthritis pain, which captures the difference in action potential shape and firing rate in response to diverse stimuli. We will screen for small molecule compounds that reverse the pain phenotype while minimizing perturbation of neuronal behavior orthogonal to the pain phenotype, the in vitro “side effects.” We will counter-screen against neurons from the cerebral cortex and cardiomyocytes from the heart to prioritize compounds that act selectively in inflamed sensory neurons. The highest ranking compounds will be chemically optimized and their pharmacokinetic, drug metabolism, and in vivo efficacy will be characterized. Our goal is to advance therapeutic discovery for pain, which may ultimately help relieve the US opioid crisis.