A Modality-Agnostic Potency Assay Enabling Both Ex Vivo and In Vivo Genome Editing Therapeutics for Sickle Cell Disease

一种与模态无关的效力测定，可实现镰状细胞病的体外和体内基因组编辑治疗

• 批准号: 10668694
• 负责人: Petros Giannikopoulos
• 金额: $ 48.95万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-28 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10668694
• 关键词: Abnormal Hemoglobins; Abnormal Red Blood Cell; Address; Affect; American; Biological Assay; Biophysics; Blood capillaries; Cells; Chemistry; Clinical; Clinical Trials; Code; DNA sequencing; Data; Development; Devices; Diagnostic; Diagnostic Equipment; Disease; Erythrocytes; Event; Exhibits; FDA approved; Feedback; Genes; Health; Hematological Disease; Hematology; Hematopoietic stem cells; Hemoglobin; High Pressure Liquid Chromatography; Human; In Vitro; Individual; Inherited; Label; Laboratories; Life Expectancy; Linear Regressions; Machine Learning; Measures; Methods; Microfluidics; Modality; Modeling; Modification; Molecular; Morbidity - disease rate; Organ; Organ failure; Outcome; Output; Pain; Pathologic; Patients; Performance; Pharmaceutical Preparations; Phenotype; Polymers; Population; Positioning Attribute; Property; Protocols documentation; Reference Standards; Regulation; Research Project Grants; Resolution; Sampling; Severities; Sickle Cell Anemia; Source; Testing; Training; Validation; Variant; algorithm training; assay development; autosome; base editing; biochip; biophysical properties; cell preparation; clinical development; clinically relevant; cohort; diagnostic assay; diagnostic tool; disease phenotype; experience; gene therapy; genome editing; health assessment; improved; in vivo; innovation; laboratory equipment; machine learning model; manufacture; mortality; neural network; next generation; novel; personalized diagnostics; polymerization; primary endpoint; repaired; response; simulation; supervised learning; therapeutic genome editing; vaso-occlusive pain

ABSTRACT / PROJECT SUMMARY Sickle-cell disease (SCD) is an autosomal recessive disorder that causes considerable morbidity and mortality, affecting an estimated 100,000 individuals in the US, and millions more worldwide. Multiple editing-based cures for SCD are currently in clinical development, however, there are no clinical-grade laboratory tests available capable of characterizing the biophysical and rheological properties of RBCs derived from genome-edited SCD HSPCs. Assays capable of characterizing RBC quality are urgently needed to assess the potency of emerging editing-based genomic therapies for SCD, regardless of the editing modality. One of the central challenges that has impeded the development of a highly performant potency assay for evaluating the functional efficacy of editing-based genomic therapies for SCD has been the lack of laboratory technologies capable of sensitively, accurately, and precisely capturing the biophysical properties of SCD-RBCs utilizing only a small number of cells. In recent years, several innovations have emerged that now make the development and analytical validation of a potency assay for editing-based SCD genomic therapies feasible. One of these has been the advent of microfluidics-based diagnostic devices capable of functionally characterizing the health of RBCs at unprecedented levels of resolution and sensitivity. This proposal seeks to leverage (1) an existing suite of these aforementioned next-generation RBC biophysical and functional characterization devices, (2) conventional hematologic assays, and (3) a well-established machine learning approach to develop and analytically validate a first-in-kind potency assay for editing-based therapies for SCD. To achieve this, we will first construct a panel of comprehensively profiled, gold-standard reference samples of HSPCs that simulate a representative range of genome editing outcomes in SCD and prepare data for machine learning training. A machine learning model will then be trained to predict the percentage of RBCs that functionally exhibit a non-SCD phenotype. Once trained, we will validate the performance of the new potency assay, a panel of HSPCs affected by SCD will be therapeutically edited using at least three different modalities (e.g. homology-directed repair, base-editing, etc.).

摘要/项目总结 镰状细胞病（SCD）是一种常染色体隐性遗传疾病， 发病率和死亡率，影响美国估计10万人，数百万人 国际吧多种基于编辑的SCD治疗目前正在临床开发中，然而， 没有临床级的实验室测试能够表征生物物理学 和源自基因组编辑的SCD HSPC的RBC的流变性质。检测试剂盒 红细胞质量的特征，迫切需要评估新兴的潜力， 用于SCD的基于编辑的基因组疗法，无论编辑方式如何。 阻碍开发高性能 用于评估SCD的基于编辑的基因组疗法的功能功效的效力测定 缺乏能够灵敏、准确和精确地 仅利用少量细胞捕获SCD-RBC的生物物理特性。在 近年来，出现了一些创新，现在使发展和分析 验证基于编辑的SCD基因组疗法的效力测定是可行的。其中一 基于微流体的诊断设备的出现， 以前所未有的分辨率和灵敏度表征RBC的健康状况。 该提案旨在利用（1）上述现有套件 下一代RBC生物物理和功能表征装置，（2）常规 血液学测定，和（3）完善的机器学习方法来开发和 分析验证SCD基于编辑疗法的首个同类效价测定。到 要做到这一点，我们将首先建立一个全面介绍，黄金标准的参考小组， 模拟SCD中代表性范围的基因组编辑结果的HSPC样品 并为机器学习训练准备数据。然后，机器学习模型将被训练成 预测在功能上表现出非SCD表型的RBC的百分比。一旦接受训练， 我们将验证新效价测定的性能，即一组受SCD影响的HSPC 将使用至少三种不同的方式（例如同源定向的 修复、基础编辑等）。