Reverse Translation of Patient Controlled Analgesia: a New Measure of Rodent Pain

描述（由申请人提供）：大约30%的美国成年人患有某种慢性疼痛。这一深刻的公共卫生问题因用于帮助控制慢性疼痛的阿片类止痛药（镇痛药）的严重副作用和滥用可能性而复杂化。因此，迫切需要新型镇痛药。最近，一种全新的镇痛药（nk1受体拮抗剂）被证明对人类无效，尽管在啮齿动物中广泛成功。这些失败只是一个更大趋势的一部分——FDA的数据显示，85%的镇痛药在人体试验中失败，而所有新药的平均失败率约为89%。这些失败很少是由于副作用或毒性。相反，在大约80%的情况下，它们根本不起作用。这些失败约占药物开发成本的75%，造成财政压力，对社会造成广泛的负面影响（包括药物成本，以及缺乏针对无利可图的疾病或人群的药物开发）。最近失败的止痛药（“止痛药”）为解决这一更广泛的问题提供了有用的经验。简单地说，每一种在人体试验中失败的药物似乎在动物身上都起作用；动物镇痛药物的发现很容易出现假阳性。其中一个原因是，用于发现新止痛药的小鼠疼痛测量与人类临床症状几乎没有对应关系。例如，在老鼠身上，我们测量的是反射反应的抑制，而不是疼痛感觉本身的抑制；但在人类身上，我们希望找到一种药物，既能减弱疼痛的感觉，又能保持基本的防伤反射功能完好无损。因此，如果我们想要在人类身上发现一种有用的止痛剂，我们实际上在老鼠身上测量的是完全错误的东西。为了解决这个问题，理想情况下，我们需要让一只老鼠评估它所经历的疼痛的严重程度和类型，就像我们在医院康复室里问人类一样，但没有语言的好处。事实上，我们已经秘密地监测了一个人类病人的疼痛，这种方法很容易转化为老鼠的方法——让病人控制自己的镇痛，观察他们自己给药的行为。在人类中，这种技术被称为“病人自控镇痛”。动物也可以选择性地服用镇痛药来控制疼痛，这种现象被称为“自我镇痛”。然而，目前的动物镇痛自我给药技术是粗糙的，不适合药物发现和翻译。因此，本项目将完善这些技术，开发出相当于老鼠的

DESCRIPTION (provided by applicant): Approximately 30% of American adults suffer some kind of chronic pain. This profound public health issue is compounded by the serious side effects and abuse potential of the opiate painkillers (analgesics) used to help manage chronic pain. Thus new kinds of analgesics are desperately needed. Recently, an entire new class of analgesics (NK1-receptor antagonists) turned out to be ineffective in humans despite widespread success in rodents. These failures are part of a wider trend - FDA data shows that 85% of analgesics fail in human trials, while the average failure rate of all new drugs is roughly 89%. Few of these failures are due to side effects or toxicity. Instead in about 80% of cases, they simply don't work. These failures represent roughly 75% of the cost of drug development, creating financial pressures that drive widespread negative impacts on society (including the cost of drugs, and the lack of drug development for unprofitable diseases or populations). Recent failed analgesics ('pain killers') provide useful lessons for solving this broader problem. Every drug that fails in human trials appeared to work in animals - simply put; analgesic drug discovery in animals is very prone to false positives. One reason for this is that the measures of pain in mice which are used to discover new analgesics bear little correspondence to human clinical symptoms. For instance in mice we measure the suppression of reflex responses rather than the suppression of the sensation of pain itself; but in humans, we want to find drugs that blunt the sensation of pain and leave essential injury-preventing reflexes intact. Thus, in mice we are actually measuring exactly the wrong things if we want to discover a useful analgesic in humans. To solve this problem we ideally need to ask a mouse to rate the severity and type of pain it is experiencing in exactly the same way that we ask humans in a hospital recovery suite, but without the benefit of language. In fact, we already covertly monitor a human patient's pain in a way that is easily converted for use in mice - by giving the patient control over their own analgesia, and observing their self-dosing behavior. In humans this technique is called 'Patient Controlled Analgesia'. Animals can also selectively consume analgesics to control pain - a phenomenon called 'Analgesic Self Administration'. However, current Analgesic Self Administration techniques in animals are crude and poorly suited to drug discovery and translation. Therefore, this project will refine these techniques to develop a mouse equivalent of Patient Controlled Analgesia, so that pain in mice can be measured in the same way it is in humans. We will develop equipment that allows the use of this technique in the home cage of group-housed mice. We will test whether it can ask mice to report the severity and type of pain they are in, and whether it would have correctly identified as failures the very drugs which recently failed in humans. The resulting technology will be made publically available as open source software and 3D printing files, so that any researcher can build this new equipment. The impacts will be profound: for researchers we will deliver a translational predictive measure of pain in the mouse; and for patients this will mean the faster delivery of more effective and cheaper drugs.