Identifying Optimal Treatment Strategies for Tuberculosis Treatment

确定结核病治疗的最佳治疗策略

• 批准号: 10320396
• 负责人: David Alland
• 金额: $ 74.29万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-16 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10320396
• 关键词: AIDS clinical trial group; Address; Adherence; Algorithms; Automobile Driving; Bacteria; Body mass index; Budgets; Caring; Categories; Centers for Disease Control and Prevention (U.S.); Characteristics; Chest; Clinical; Clinical Trials; Complement; Concentration measurement; Data; Data Analyses; Data Collection; Data Set; Databases; Development; Disease; Disease Marker; Dose; Drug Kinetics; Drug Tolerance; Drug resistance; Drug resistance in tuberculosis; Drug toxicity; Drug usage; Early treatment; Engineering; Ensure; Ethambutol; Event; Financial Support; Funding; Future; Genome; Genus Mycobacterium; Goals; Grant; Growth; HIV; Health system; Individual; Intervention; Investigation; Leadership; Learning; Link; M. tuberculosis genome; Measurement; Measures; Microbiology; Modeling; Modernization; Moxifloxacin; Multidrug-Resistant Tuberculosis; Mutation; Mycobacterium tuberculosis; Outcome; Patient Schedules; Patients; Pharmaceutical Preparations; Pharmacodynamics; Pharmacology; Phase; Phenotype; Population; Prediction of Response to Therapy; Public Health; Pyrazinamide; Recording of previous events; Regimen; Relapse; Research Design; Rifampin; Risk; Safety; Sampling; Severities; Severity of illness; Sputum; Techniques; Testing; Therapeutic; Time; Toxic effect; Treatment Failure; Treatment Protocols; Treatment outcome; Tuberculosis; United States National Institutes of Health; Variant; Work; advanced analytics; base; clinical care; combinatorial; comparative efficacy; compliance behavior; computerized tools; cost; data access; digital health; drug-sensitive; efficacy evaluation; high risk; improved; individualized medicine; industry partner; innovation; isoniazid; minimal inhibitory concentration; novel; novel marker; optimal treatments; participant enrollment; patient oriented; patient population; patient subsets; patient variability; persistent bacteria; pharmacodynamic model; pharmacokinetic model; phase III trial; public health priorities; pyrazinoic acid; radiological imaging; rate of change; relapse risk; response; rifapentine; risk stratification; standard of care; success; time use; tool; treatment duration; treatment optimization; treatment response; treatment strategy; tuberculosis drugs; tuberculosis treatment

Project Summary/Abstract The current standard of care for drug-sensitive TB is a “one-size-fits-all” approach, putting hard-to-treat patients at higher risk of relapse and mycobacteria at higher risk of acquiring drug resistance. The Phase 3 treatment-shortening study TBTC/ACTG (Study 31/A5349) is evaluating the efficacy and safety of two new short-course regimens containing high-dose rifapentine. The primary aim of our proposal is to embed full pharmacology and microbiology analyses (PK/PD) in this clinical trial to provide detailed drug pharmacokinetic, MIC response and safety data - including novel data (markers of persisters) for more than 2,000 patients. Our goal is to understand and quantify the interactions among individual drug PK/PD, MICs, new markers of genome load, new markers for persisters, active disease severity and early treatment response in a diverse patient population and recognize how they relate to clinical outcome and safety events. By doing so, we will be able to understand and quantify the contributions of pharmacological (multidrug pharmacokinetic) and non- pharmacological (host, disease severity) components of treatment response and to understand the phenotypes of patients who are hard to treat, allowing us to derive optimal treatment strategies for all patients with drug- sensitive TB, including choice of regimen, treatment duration, and dose. We propose the innovative hypothesis that both the infecting bacteria and the host can be seen as “low” and “high” risk and that it is the combination of these two risks that together determine treatment outcome and the required duration of treatment, regardless of the drugs used. Our approach will stratify bacterial risk by burden, MIC - even among drug-susceptible Mtb - and the presence of drug-tolerant subpopulations. The host risk will be stratified by disease severity, HIV status and ability to absorb and metabolize drugs (PK). We will then use advanced analytic and modeling strategies to develop tools and algorithms to identify low-risk patients infected with low-risk bacteria who can be treated with ultra-short treatment (<=four months) and high-risk patients infected with high-risk bacteria who will need treatment for longer than six months. Through our analyses, we will be able to select for each patient the regimen that results in the highest likelihood of cure. Our findings will completely change the future of TB clinical trials and care worldwide. This study will address fundamental questions, such as what the exposure-response/safety relationships and favorable AUC/MIC targets are for all first-line TB drugs using a major clinical outcome (relapse) and how early response to treatment relates to clinical outcome in a large and diverse patient population. The project has unprecedented support from the TBTC/ACTG leadership and our industry partner (Sanofi Aventis). The funds in this R01 requests the budget needed to complete drug measures and MIC not included in Study 31 (i.e., all drugs other than rifapentine and moxifloxacin) and the full suite of PK/PD modeling and learnings that go beyond the trial's primary goal of testing the non-inferiority of the experimental four-month regimens.

项目概要/摘要 目前药物敏感结核病的护理标准是“一刀切”的方法，使难以治疗的结核病 复发风险较高的患者和获得耐药性风险较高的分枝杆菌。 治疗缩短研究 TBTC/ACTG（研究 31/A5349）正在评估两种新药物的有效性和安全性 含有大剂量利福喷丁的短程治疗方案的主要目的是嵌入完整的治疗方案。 本临床试验中的药理学和微生物学分析（PK/PD）可提供详细的药物药代动力学、 MIC 反应和安全性数据 - 包括 2,000 多名患者的新数据（持久性标志物）。 目标是了解和量化单个药物 PK/PD、MIC、新标记物之间的相互作用 基因组负载、持续者的新标记、活跃疾病的严重程度和多种疾病的早期治疗反应 患者群体并认识到他们与临床结果和安全事件的关系。 能够理解和量化药理学（多药药代动力学）和非药理学的贡献 治疗反应的药理学（宿主、疾病严重程度）组成部分并了解表型 难以治疗的患者，使我们能够为所有患有药物的患者制定最佳治疗策略 敏感结核病，包括治疗方案的选择、治疗持续时间和剂量。 我们提出了一个创新的假设：感染细菌和宿主都可以被视为“低” 和“高”风险，这两种风险的组合共同决定了治疗 无论使用何种药物，我们的方法都会根据结果和所需的治疗持续时间进行分层。 按负担划分的细菌风险、MIC（甚至在药物敏感 Mtb 中）以及耐药性的存在 宿主风险将根据疾病严重程度、艾滋病毒状况以及吸收和吸收能力进行分层。 然后我们将使用先进的分析和建模策略来开发工具和代谢药物（PK）。 识别感染低风险细菌的低风险患者的算法，这些患者可以接受超短期治疗 （<=四个月）以及感染高危细菌且需要治疗时间超过 通过我们的分析，我们将能够为每位患者选择效果最好的治疗方案。 我们的研究结果将彻底改变全世界结核病临床试验和护理的未来。 这项研究将解决基本问题，例如暴露-反应/安全关系 有利的 AUC/MIC 目标适用于所有一线结核病药物，使用主要临床结果（复发）以及如何 该项目对治疗的早期反应与大量不同患者群体的临床结果有关。 来自 TBTC/ACTG 领导层和我们的行业合作伙伴（赛诺菲安万特）的前所未有的支持。 该 R01 请求完成研究 31 中未包括的药物措施和 MIC 所需的预算（即所有 除利福喷特药物和莫西沙星外）以及全套 PK/PD 建模和学习 该试验的主要目标是测试四个月实验方案的非劣效性。