De facto monotherapy during multidrug TB treatment and emergence of resistance

描述(申请人提供)：简单的药物敏感型结核病(TB)必须用最多四种药物治疗，以防止出现耐药性。然而，耐药性正在上升，全球多药耐药和广泛耐药病例不断增加。由于大量的药片负担和漫长的治疗导致的依从性差，这在很大程度上被归咎于耐药结核病的升级。虽然这可能是一个促成因素，但很可能是宿主和病原体固有的因素也推动了耐药性的出现。我们建议的研究将调查以下四个因素对药物开发的贡献 结核病损一级的耐药性：(1)具有突变的临床结核分枝杆菌(Mtb)菌株，其最低抑菌浓度(MIC)略有增加，远低于通常确定耐药性的最低抑菌浓度下限；(2)患者之间的药物暴露差异；(3)异质药物 在病变间隔内的分布；以及(Iv)药物诱变。我们建议确定这些因素如何相互作用，在体外选定的利基环境和活动性空洞性结核病的兔模型中创造事实上的单一疗法。在体外，我们将建立Mtb菌株在敏感性逐步下降后从完全敏感进化到完全耐药的途径，具有明确突变的Mtb菌株可能会模拟几种不同的临床耐药风险情景。令人惊讶的是，氟喹诺酮类药物的潜力 DNA损伤增加耐药突变的频率在结核分枝杆菌中尚未被探索，而它在其他细菌物种中是很好的特征。由于氟喹诺酮类药物 被认为是结核病治疗的新支柱，无论是对药物敏感的疾病还是耐药疾病，我们将填补这一空白，并将我们的体外研究结果转化为兔模型，使用单一药物治疗和联合治疗。我们将使用一个优化的慢性活动性结核病兔模型，该模型概括了人类结核病的主要病理特征：实性细胞肉芽肿、坏死性纤维病变和空洞。该模型非常适合于查询以病变为中心的微生物学、遗传耐药性、药物渗透和菌株特异性多态的读数。我们将把我们的研究重点放在目前被认为是治疗药物敏感和耐药结核病的临床开发中最有前景的三种药物组合上。该方案结合了氟喹诺酮类药物莫西沙星、吡津酰胺和硝基咪唑PA-824。利用药物计量学的方法，我们将建立一个药代动力学-药效学模型，该模型集成了微小的MIC增加、血浆和皮损PK变异性、药物诱变以及与出现耐药相关的药物空间分布。通过预测事实上的单一疗法的风险，该模型将在电子计算机中预测安全的个体化人类组合，以防止在治疗活动性结核病期间获得耐药性。我们的意图是，未来这一方法的使用将把药物/剂量方案的设计从经验性转变为合理性，同时降低发生耐药性的风险。

DESCRIPTION (provided by applicant): Uncomplicated drug-sensitive tuberculosis (TB) must be treated with up to four drugs to prevent emergence of drug resistance. Yet, resistance is on the rise, with multi-drug and extensively-drug resistant cases increasing globally. Poor compliance due to a large pill burden and lengthy therapy has been largely blamed for the escalation of drug-resistant TB. While this is probably a contributing factor, it is likely that fators intrinsic to the host and pathogen also drive the emergence of drug resistance. Our proposed research will investigate the contribution of the following four factors to the development of drug resistance at the level of the TB lesion: (i) clinical Mycobacterium tuberculosis (Mtb) strains wit mutations that produce small increases in MIC which are well below MIC cutoffs that usually identify drug resistance; (ii) inter-patient variability in drug exposure; (iii) heterogeneous drug distribution within lesion compartments; and (iv) drug induced mutagenesis. We propose to determine how these factors interact to create de facto monotherapy in selected niches in vitro and in the rabbit model of active cavitary TB. In vitro, we will establish the routes by which Mtb strains evolve from fully susceptible to fully resistant following a stepwise decline of susceptibility, with Mtb strains that have defined mutations likely to emulate several different clinical scenarios of drug-resistance risk. Surprisingly, the potential of fluoroquinolone-mediated DNA damage to increase the frequency of resistance-conferring mutations has not been explored for Mtb, while it is well-characterize for other bacterial species. Since fluoroquinolones are being considered as the new backbone for TB therapy, both for drug susceptible and drug resistant disease, we will fill this gap and translate our in vitro findings in the rabbit model, uing single drug treatment and combination therapy. We will use an optimized rabbit model of chronic active TB which recapitulates the major pathological features of human TB: solid cellular granulomas, necrotic fibrotic lesions and cavities. The model is ideally suited to query lesion-centric read-outs of microbiology, genetic resistance, drug penetration, and strain-specific polymorphisms. We will focus our studies on the three-drug combination currently viewed as among the most promising in clinical development for drug-sensitive and drug-resistant TB. This regime combines the fluoroquinolone moxifloxacin, pyrazinamide and the nitroimidazole PA-824. Using pharmacometrics approaches, we will build a pharmacokinetic-pharmacodynamic model that integrates small MIC increases, plasma and lesion PK variability, drug-induced mutagenesis and spatial drug distribution in relation to emergence of resistance. By predicting the risk of de facto monotherapy, the model will inform in silico predictions of safe individualize human combinations that prevent acquisition of drug resistance during treatment of active TB. It is our intent that future use of this approach will shift the paradigm from empirical to rational design of drug/dosing regimens with decreased risk for the development of drug resistance.