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.

项目概要/摘要 在 P01 AI123036 中，我们能够生成一种算法，对分枝杆菌的单个药剂进行排名 结核病 (MTB)，确定了有前途的 2 种药物组合，并采用全新的数学方法 方法，确定了 3 种药物治疗方案预计明显优于 2 种药物治疗方案。 在 BALB/c 模型 (H37Rv) 和 MTB 非人类灵长类动物模型 (Erdman 在这个提案中，我们将扩展我们之前的工作。 有大量新的 MTB 药物，其中许多具有新颖的作用机制，我们有 4 个具体目标。 （SA），完成后，我们将能够识别多种药物组合，从而优化杀灭率 生物体处于3种不同的代谢状态，会抑制耐药性的出现。 在中空纤维感染模型 [HFIM] (SA#1) 中，我们将能够根据效力对新药剂进行排名 HFIM 可以深入了解药物的杀灭和暴露反应。 我们确定了一种接近最佳的 3 种药物治疗方案（PMD/MFX/BDQ）。 我们可以研究用新药物替代旧药物，并且我们可以扩展治疗方案以确定近乎有效的药物 最佳的 4 种药物治疗方案对于细菌负荷高的患者尤其重要。 在 SA #2 中，我们将在两种小鼠模型（BALB/c 和 C3HeB/FeJ 小鼠）中测试 SA#1 的方案。 两者都提供了有关杀死和抑制克拉姆尼克小鼠的信息。 我们将使用基质辅助激光解吸来进行更多的病理学重新组装。 电离 MS 成像和激光捕获显微切割 LCMS 可以识别空间分布。 和药物的量化有关治愈的一个问题是要等待多长时间才能牺牲动物来记录。 一些药物（BDQ）的组织半衰期很长，我们将记录药物的进入/排出率。 进入感染部位，从而确定何时可以牺牲动物群来记录根除情况。 在 SA #3 中，我们将定量记录抗菌作用的机制，我们已经产生了第一个-。 我们还开发了 MTB 中 PBP 结合的动态模型，并将其与细胞杀伤率联系起来。 AMP/ADP/ATP 细胞内检测将用于二芳基喹啉（例如 BDQ）和 PMD 等药物。 充当能量毒物（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，将它们与单独治疗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建模，在 SA #4 中，我们编写了代码来扩展早期的分析， 对于这些高维模型，我们开发了几种方法来实现从 3 种药物到 4 种药物的治疗方案。 加快分析速度，使它们在计算上易于处理。在提案结束时，我们将开发一种 4 种药物算法。 允许快速识别适用于易感人群和不易感人群的近乎最佳的治疗方案 该算法将适用于今天的智能体，也适用于已发现的智能体。