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

根据 PET 数据验证占用图像。

• 批准号: 10612763
• 负责人: Evan D Morris
• 金额: $ 59.78万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612763
• 关键词: Adopted; Affinity; Algorithms; Binding; Binding Sites; Biological; Brain; Brain imaging; Brain region; Characteristics; Collaborations; Data; Databases; Dependence; Development; Dose; Drug Industry; Drug Targeting; Enzymes; Functional Imaging; Goals; Human; Image; Individual; Industrialization; Intervention; Knowledge; Location; Manuals; Measures; Methods; Noise; Outcome; Output; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Positioning Attribute; Positron-Emission Tomography; Predisposition; Primates; Provider; Research; Research Design; Resolution; Resources; Site; Spatial Distribution; Speed; Statistical Methods; Target Populations; Technology; Testing; Therapeutic; Tracer; Translating; Translations; Validation; Variant; Work; archived data; cost; design; drug action; drug candidate; drug development; drug discovery; drug testing; experience; experimental study; image registration; in vivo; in vivo imaging system; industry partner; innovation; interest; invention; nonhuman primate; novel; novel therapeutics; practical application; receptor; response; simulation; skills; standard measure; uptake

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.

抽象的 PET 成像在 CNS 药物开发中最有用的应用是测量新药的占用率 目标结合位点（例如受体、转运蛋白和酶）的候选物。这些目标入住率 (TO) 研究 - 通常从灵长类动物开始并进展到人类的第一阶段 - 对体内剂量非常有帮助 - 发现、决定是否将候选化合物推进成本更高的后期试验，并优化 后期研究的设计。当前技术水平：一种通用且信息丰富的分析方法 TO 数据是“拉森图”。拉森图产生两点估计：目标的部分占用率 通过药物 (ODrug) 和示踪剂 (VND) 的不可置换摄取。这种流行背后的假设 方法是 (a) 两种测量在整个大脑中是一致的，并且 (b) PET 示踪剂与 与候选药物相同的靶位点群体。技术差距：有重要案例 违反了拉森图的一项或多项假设。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。 实验室的基本开发：在耶鲁大学的研究小组中，我们开发了 标准拉森图提供有关 ODrug 和 VND 局部变化的信息。我们的成果 新的“Lassen Plot Filter”（LPF）算法是 ODrug、VND 和 EC50 的逐个体素估计（即“占用率”） 图像”，“不可置换的摄取和药物亲和力，图像”）。我们相信这些新颖的图像代表了很多 TO 研究的结果比确定最大精确位置的标准测量结果更丰富 药物的具体作用。例如，当违反假设时，占用图像的偏差将较小 比点估计。新图像可以作为更丰富的端点来推动继续/不继续的决策 候选化合物基于对具有最大治疗意义的特定大脑位置的药物作用。 学术-工业合作伙伴关系。我们的工业合作伙伴是一家在开展业务方面拥有丰富经验的公司 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档案数据，用于测试和 验证我们的 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/或违反标准假设的档案数据。 (3)执行 对灵长类动物进行有限的研究，以证实我们的新图像的生物学解释。这项工作将是 当我们完全表征并优化 LPF 算法的性能后，就完成了。在漫长的 术语，我们的目标是对 TO 研究的逐体素分析进行​​验证，得到广泛采用， 最终用户的利益，加速药物开发。