Validation of Occupancy Images from PET Data. A Novel Endpoint for Drug Discovery

摘要 PET成像在CNS药物开发中最有用的应用是测量新药的占有率 靶结合位点的候选物（例如，受体、转运蛋白和酶）。这些目标占用率（TO） 研究-通常从灵长类动物开始，在人类中进展到1期-对体内剂量非常有帮助- 寻找，决定是否将候选化合物推进到更昂贵的后期试验，并优化 后期研究的设计。当前最新技术水平：一种常见的信息分析方法， TO数据是“拉森图”。Lassen图产生两个点估计： 药物（ODrug）和示踪剂（VND）的不可替代摄取。这种流行的假设 方法是（a）两种测量在整个大脑中是均匀的，以及（B）PET示踪剂结合到脑组织中。 与候选药物相同的靶位点群体。技术差距：有一些重要的案例， 违反了拉森图的哪一个或多个假设。在这种情况下，（1）TO研究的结果 可能有偏见，（2）可能需要人工干预，（3）正确的解释将取决于先前的 目标亚型的空间分布的知识，并且在任何情况下，（4）标准方法几乎没有提供 没有关于ODrug区域差异的信息。 实验室中的基本开发：在我们耶鲁大学的研究小组中，我们开发了一种扩展的 标准Lassen图，提供关于ODrug和VND的局部变化的信息。我们的成果 新的“Lassen Plot Filter”（LPF）算法是ODrug、VND和EC 50的逐体素估计（即，占有率 图像“，”不可替代的摄取，和药物亲和力，图像“）。我们相信这些新奇的图像 TO研究的结果比标准措施更能提供信息， 药物的具体作用。例如，当假设被违反时，占用图像将不那么有偏见 比点估计。新的图像可以作为更丰富的端点，以推动进行/不进行决策 候选化合物基于在最具治疗意义的特定脑位置处的药物作用。 学术-工业伙伴关系。我们的工业合作伙伴，一家在开展 TO研究将为我们提供非常有价值的人类和非人类灵长类动物的档案数据， 验证LPF算法 在本项目中，我们将（1）分析具有已知占用分布的模拟数据。(2)重新分析 代表不同案例和/或违反标准假设的归档数据。(3)执行 在灵长类动物中进行限制性研究，以证实我们对新图像的生物学解释。这项工作将 当我们充分描述并优化了LPF算法的性能时，我们就完成了。从长远 长期而言，我们的目标是对TO研究的逐体素分析进行验证，以广泛采用， 最终用户的利益，以加速药物开发。

Abstract The most useful application of PET imaging in CNS drug development is to measure occupancy of new drug candidates at target binding sites (e.g., receptors, transporters, and enzymes). These target occupancy (TO) studies -often starting in primates and progressing to Phase 1 in humans - are very helpful for in vivo dose- finding, deciding whether to advance a candidate compound to more costly later phase trials, and optimizing the design of later phase studies. Current State of the Art: A common and informative approach to analysis of TO data is the “Lassen plot”. The Lassen plot yields two point estimates: a fractional occupancy of the target by the drug (ODrug) and the nondisplaceable uptake of the tracer (VND). Assumptions underlying this popular method are that (a) both measures are uniform across the whole brain and (b) the PET tracer binds to the identical population of target sites as the candidate drug. Technology Gap: There are important cases in which one or more assumption of the Lassen plot is violated. In such cases, (1) the outcome of the TO study may be biased, (2) manual intervention may be required, (3) proper interpretation will depend on prior knowledge of the spatial distribution of target subtypes, and in any case, (4) the standard method offers little to no information on regional variation in ODrug. Basic development in the lab: In our research group at Yale, we have developed an extension of the standard Lassen plot that provides information about local variation in ODrug and VND. The outcomes of our new “Lassen Plot Filter” (LPF) algorithm are voxel-by-voxel estimates of ODrug, VND and EC50 (i.e., `occupancy images', `nondisplaceable uptake, and drug affinity, images'). We believe these novel images represent much more informative outcomes of TO studies than standard measures for identifying precise locations of maximal specific action of drugs. For example, when assumptions are violated, occupancy images will be less biased than point estimates. The new images could serve as richer endpoints to drive go/no-go decisions on candidate compounds based on drug action at specific brain locations of greatest therapeutic interest. Academic-Industrial Partnership. Our industrial partner, a company with extensive experience in conducting TO studies, will provide us with very valuable archival data in humans and nonhuman primates for testing and validating our LPF algorithm. In the present project, we will (1) Analyze simulated data with known occupancy distributions. (2) Re-analyze archival data that represent different cases and/or violations of standard assumptions. (3) Perform circumscribed studies in primates to confirm the biological interpretations of our new images. The work will be complete when we have fully characterized and optimized the performance of our LPF algorithm. In the long term, our goal is for a validated version of our voxel-by-voxel analysis of TO studies, to be adopted widely, to the benefit of end-users, to speed drug development.