Optimizing Multi-drug Mycobacterium tuberculosis Therapy for Rapid Sterilization and Resistance Suppression

优化结核分枝杆菌多药治疗以实现快速灭菌和耐药性抑制

• 批准号: 10567327
• 负责人: George Louis Drusano
• 金额: $ 131.43万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-25 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10567327
• 关键词: Address; Algorithms; Amino Acyl-tRNA Synthetases; Animals; Antimicrobial Effect; Bacteria; Binding; Biological Assay; C3HeB/FeJ Mouse; Carbapenems; Catabolism; Cell Wall; Cells; Cholesterol; Code; Combination Drug Therapy; Combined Modality Therapy; Complex; Data; Drug Combinations; Drug Exposure; Equation; Evaluation; Excision; Experimental Designs; Fiber; Foundations; Human; Image; In Vitro; Inbred BALB C Mice; Infection; Kinetics; Lesion; Link; Measures; Metabolic; Modeling; Monobactams; Mus; Mycobacterium tuberculosis; New Agents; Oral; Organism; Pathologic; Pathology; Pathway interactions; Patients; Penetration; Pharmaceutical Preparations; Phase; Poison; Population; Predisposition; Primary Infection; Property; Publishing; Regimen; Resistance; Rest; Site; Spatial Distribution; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Speed; Sterilization; Structure of parenchyma of lung; Testing; Time; Tissues; Tuberculosis; Validation; Work; Writing; base; beta-Lactams; cell killing; cohort; data modeling; dosage; drug distribution; efficacy study; experimental study; flasks; high dimensionality; in vivo; inhibitor; insight; laser capture microdissection; leucine-tRNA; liquid chromatography mass spectroscopy; man; mass spectrometric imaging; mathematical methods; mathematical model; mouse model; nonhuman primate; novel; prospective; receptor binding; response; success; supercomputer; therapy duration; tuberculosis treatment

Project Summary/Abstract In P01 AI123036, we were able to generate an algorithm that ranked single agents for Mycobacterium tuberculosis (MTB), identified promising 2-drug combinations and, with a completely novel mathematical approach, identified 3-drug regimens predicted to be significantly better than 2-drug regimens. These predictions were prospectively validated in a BALB/c model (H37Rv) and in a Non-Human Primate model of MTB (Erdman strain). In this proposal, we will extend our previous work. There is a large number of new MTB agents, many with novel mechanisms of action. We have 4 Specific Aims (SA) that, when complete, will allow us to identify multi-drug combinations that will optimize rate of kill for organisms in 3 different metabolic states and will suppress resistance emergence. In the Hollow Fiber Infection Model [HFIM] (SA#1), we will be able to rank new agents on the bases of potency and physicochemical properties. The HFIM provides insight into the drug’s exposure-response for kill and resistance suppression. We identified a near optimal 3-drug regimen (PMD/MFX/BDQ). With new single agents, we can examine substituting a new agent for an older agent AND we can expand the regimens to identify a near- optimal 4-drug regimen. This will be particularly important for patients with high bacterial burdens. In SA #2, we will test regimens from SA#1 in two murine models (BALB/c & C3HeB/FeJ mice). These will give somewhat different information. Both give information regarding kill and resistance suppression. Kramnik mice have pathology more closely resembling that in humans. We will use Matrix-Assisted Laser Desorption Ionization-MS Imaging and Laser Capture Microdissection LCMS. This allows identification of spatial distribution and quantification of drugs. A question regarding cure is how long to wait to sacrifice animals to document eradication. Some agents (BDQ) have long tissue half-lives. We will document rates of ingress/egress of drugs into the infection site, allowing determination when animal cohorts may be sacrificed to document eradication. In SA #3, we will document mechanisms of antimicrobial effect quantitatively. We have generated a first-of-a- kind dynamic model for PBP-binding in MTB, and will link this to rates of cell kill. We have also developed AMP/ADP/ATP intracellular assays. These will be employed for agents like diarylquinolines (e.g. BDQ) and PMD that act as energy poisons (for PMD, this occurs under anaerobic/non-replicative conditions. We will measure intracellular (MTB) drug concentrations, linking them to effect alone and in combination therapy experiments. Proposal success rests on modeling of the data. In SA #4, we have written code to extend earlier analyses, going from 3- to 4-drug regimens. For these high dimensional models, we developed several approaches to speed up analysis making them computationally tractable. At proposal end, we shall develop a 4-drug algorithm allowing rapid identification of near optimal regimens that work for both susceptible and less-susceptible organisms. The algorithm will be general. It will work well for today’s agents but also for agents as discovered.

项目总结/摘要 在P01 AI 123036中，我们能够生成一种算法， 结核病（MTB），确定了有前途的2-药物组合，并与一个全新的数学 方法，确定了3种药物方案，预测显著优于2种药物方案。这些预测 在BALB/c模型（H37 Rv）和MTB的非人灵长类动物模型（Erdman 应变）。在本提案中，我们将扩展我们以前的工作。 存在大量新的MTB药剂，其中许多具有新颖的作用机制。我们有四个具体目标 (SA)完成后，将使我们能够确定多种药物组合， 生物体处于3种不同的代谢状态，并将抑制耐药性的出现。 在中空纤维感染模型中，我们将能够根据效力对新药剂进行排名 和物理化学性质。该抑制剂提供了对药物的杀灭反应的深入了解， 阻力抑制我们确定了一个接近最佳的3种药物方案（PMD/MFX/BDQ）。有了新的单一代理人， 我们可以用一种新的药物代替一种旧的药物，我们可以扩大治疗方案，以确定一种接近- 最佳4药方案。这对于细菌负荷高的患者尤其重要。 在SA#2中，我们将在两种鼠模型（BALB/c和C3 HeB/FeJ小鼠）中测试来自SA#1的方案。这些会给 有些不同的信息。两者都给出了关于杀死和抵抗压制的信息。Kramnik小鼠 其病理学与人类更为相似。我们将使用基质辅助激光解吸 电离-MS成像和激光捕获显微切割LCMS。这允许识别空间分布 和药物的定量。关于治愈的一个问题是要等多久才能用动物献祭来记录 根除一些药剂（BDQ）具有长的组织半衰期。我们将记录药物的进出率 进入感染部位，允许确定何时可以处死动物队列以记录根除。 在SA #3中，我们将定量记录抗菌作用的机制。我们创造了第一个 一种MTB中PBP结合的动态模型，并将其与细胞杀伤率联系起来。我们还开发了 AMP/ADP/ATP细胞内测定。这些将用于二芳基喹啉（例如BDQ）和PMD等药剂 作为能量毒物（对于PMD，这发生在厌氧/非复制条件下。我们将测量 细胞内（MTB）药物浓度，将它们与单独和联合治疗实验中的效果联系起来。 提案的成功取决于数据的建模。在SA #4中，我们编写了代码来扩展先前的分析， 从3种药物方案到4种药物方案。对于这些高维模型，我们开发了几种方法， 加快分析速度，使其在计算上易于处理。在提案结束时，我们将开发一个4药物算法 允许快速识别对易感和不太敏感的人都有效的接近最佳的方案， 有机体算法将是通用的。它不仅适用于当今的代理人，也适用于所发现的代理人。