SYNERGISM AND MEDICATIONS DEVELOPMENT FOR DRUG ABUSE

描述(改编自申请者的摘要)：这是一个2倍的修订版 来自一名研究人员的申请，他取得了重大和开创性的成就 对定量评估药物相互作用的贡献。在过去的几年里 复习后，得分为211分(第29个百分位数)。当两种或两种以上的药物 由于明显相似的作用(例如，两种止痛剂)一起出现， 组合可以协同作用，也就是说，给一个夸张的 回应。协同作用在临床上很重要，尤其是如果 适用于这种组合的副作用；例如，一种新药 为治疗药物滥用而开发的药物可能与其他 病人正在服用的药物。区分协同论的方法论 来自简单的相加交互作用是复杂的，因为在 数据、不精确的效果测量(S)和药物和药物的极端多样性 用于研究它们的实验设计。该项目的目标是解决这些问题 通过发展统计/理论方法的问题， 所需的关联实验设计和一套全面的计算机 指导实验和分析数据的程序。私家侦探，谁是 既是药理学家也是数学家，他的背景是 由于与微软长期合作而产生的问题 以及他自己在统计设计和编程方面的工作 发展。其目标包括量化和分析两个量化指标 (全有或全无)效应和分级药物效应与新的统计发展， 这是一个在很大程度上被忽视的领域。与经典作品形成对比的是 20世纪20年代的S和30年代的S，主要是简单地讨论农药 线性回归模型和量化终点(%KILL)，申请人的 方法不限于简单的平行线回归，而是 允许在药物剂量效应数据中常见的多样性 会影响行为、痛感和免疫系统。一个主要目标是 扩展了概率位理论，这是一种强大的加权回归程序 适用于来自可测量端和观测端的量子数据 由药物引起的积分。药代动力学考虑是另一个目标 自给药途径以来，剂量的时间和动力学曲线 每一种试剂都会对组合实验产生深远的影响。此外，一种药物 从理论上讲，在两个部位给药相当于一种药物组合 这种现场-现场方法的分析、探索和进一步发展 为照明机构提供了一个重要的新工具；这也是一个 拟议研究的具体目标是发展普遍的、 计算驱动的组合分析指南，它将提供一种 路线图适用于几乎所有的组合和现场研究。这 GUIDE是本修订申请的最新目标。

DESCRIPTION (adapted from applicant's abstract): This is a 2x revised application from an investigator who has made significant and seminal contributions to quantitatively evaluating drug interactions. During the last review, a score of 211 (29th percentile) was awarded. When two or more drugs with overtly similar actions (e.g., two analgesics) are present together the combination may interact synergistically, that is, give an exaggerated response. Synergism is important clinically and is especially important if it applies to adverse effects of the combination; for example, a new drug developed to treat drug abuse may interact synergistically with other medications that the patient is on. Methodology for distinguishing synergism from simple additive interactions is complicated by high variability in the data, imprecise measures of effect(s) and extreme diversity in the drugs and experimental designs used to study them. This project's goal addresses these problems through the development of statistical/theoretical methodology, the associated experimental design needed and a comprehensive set of computer programs that guide the experiments and analyze the data. The P.I., who is both a pharmacologist and a mathematician, brings a background that addresses the problems by virtue of a long history of collaborations with experimentalists and by his own work in statistical design and program development. The aims include the quantitation and analysis of both quantal (all-or-none) effects and graded drug effects with new statistical development, an area that has been largely neglected. In contrast to the classic work of the 1920's and 1930's, which was largely concerned with pesticides in simple linear regression models and a quantal end point (% killed), the applicant's approached is not restricted to simple parallel-line regressions, instead allowing for the diversity that is commonly seen in dose-effect data from drugs that affect behavior, pain sensation and the immune system. A major aim is the expansion of probit theory, a powerful weighted regression procedure that is applicable to quantal data from both the measurable and observational end points induced by drugs. Pharmacokinetic considerations represent another aim since route of administration, the timing of doses and the kinetic profile of each agent profoundly affect combination experiments. Further, a single drug administered at two sites is theoretically equivalent to a drug combination analysis and exploration and further development of this site-site approach provides an important new tool for illuminating mechanism; this is also a specific aim of the proposed studies as is the development of universal, compute-driven, guide to combination analysis that will provide a kind of roadmap applicable to virtually all combination and site-site studies. This guide is the newest aim of this revised application.