Resistance Suppression for P. Aeruginosa using Novel Combination Therapy Modeling

使用新型组合疗法模型抑制铜绿假单胞菌的耐药性

• 批准号: 7513833
• 负责人: George Louis Drusano
• 金额: $ 78.79万
• 依托单位: ORDWAY RESEARCH INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7513833
• 关键词: Accounting; Affect; Aminoglycosides; AmpC beta-lactamases; Animals; Anti-Infective Agents; Antibiotic Resistance; Antibiotics; Antimicrobial Effect; Area; Carbapenems; Categories; Cefepime; Cephalosporins; Clinical; Collection; Combination Chemotherapy; Combined Modality Therapy; Data; Development; Dose; Drug Combinations; Drug Kinetics; Drug resistance; Fiber; Fluoroquinolones; HIV; Human; In Vitro; Infection; Intensive Care Units; Knowledge; Laboratories; Lactams; Learning; Levaquin; Lung; Meropenem; Microbe; Modeling; Mono-S; Morbidity - disease rate; Multi-Drug Resistance; Mus; Mycobacterium tuberculosis; New Agents; Organism; Patients; Performance; Pharmaceutical Preparations; Pharmacodynamics; Pneumonia; Population; Probability; Process; Production; Protein Overexpression; Pseudomonas; Pseudomonas aeruginosa; Research Personnel; Resistance; Schedule; Sister; Site; Surface; System; Testing; Therapeutic; Therapeutic Agents; Time; Tobramycin; Translating; Treatment Protocols; Validation; Ventilator; Work; antimicrobial drug; base; data modeling; design; dosage; drug development; efflux pump; in vivo; innovation; killings; man; mathematical model; mortality; mouse model; mutant; novel; pathogen; prevent; prospective; research study; resistance mechanism; simulation

DESCRIPTION (provided by applicant): Pseudomonas aeruginosa is a major cause of morbidity and mortality in the ICU, particularly among patients with Ventilator-Associated Pneumonia. Many isolates are multi-drug resistant and some isolates are resistant to all currently extant anti-infective agents. There are currently no new antibiotics in clinical development (in man) with novel mechanisms of action against Pseudomonas. Given the cycle time associated with new drug development, it is likely that no antibiotics with new mechanisms of action for this pathogen will arise for 5 - 7 years. Thus, we must generate new knowledge about how best to suppress antibiotic resistance for this pathogen. This will help preserve our current drugs while we await new agents. Also, when agents with new mechanisms of action become available they can be developed in an optimal fashion for resistance suppression, both as monotherapy and in combination. In this application (Specific Aim #1), we hypothesize that we can identify optimal doses and schedules of administration for monotherapy for resistance suppression by studying this pathogen in our Hollow Fiber Infection Model (HFIM) and fitting a large mathematical model to the HFIM data to identify these doses and schedules. We further hypothesize that different resistance mechanisms will alter optimal doses and schedules. We propose to study isogenic mutants of the wild-type P. aeruginosa PAO-1 isolate, each containing a defined resistance mechanism. These findings will be bridged to man through use of Monte Carlo simulation (MCS). In Specific Aim #2, we propose to examine drugs in combination chemotherapy. We have developed a completely novel mathematical model that allows description of the impact of two drug combination chemotherapy on isolates of P. aeruginosa. This model is a mixture model and allows the fitting of the model to the concentration-time course of both agents as well as to fit the model to the disparate changes over time wrought by the combination of agents on the susceptible and less-susceptible populations of organisms present. Robust identification of the parameters of this system will allow calculation of optimal combination regimens for resistance suppression. Such regimens will be bridged to man through the use of MCS, as above. The HFIM is an in vitro system. In Specific Aim #3, we will also validate these optimal and non-optimal regimens in a neutropenic mouse pneumonia model, employing the same isolates studied in vitro in Aims #1 and #2. In examining this, we will use "humanized" dosing for the regimens, so that differences between mouse and human pharmacokinetics will not drive an improper inference. This will be done for both mono- and combination therapy. Prospective validation experiments will be designed and carried out. Results will be compared with the in vitro findings and also bridged to man. In so doing robust principles will be defined for drug regimens that will suppress amplification of resistant mutant populations. Pseudomonas aeruginosa is a pathogen of major importance in the Intensive Care Unit and is often resistant to many or even all of the drugs in our therapeutic armamentarium. As no agents with a unique mechanism of action active against Pseudomonas are expected for at least 7 years, it is imperative to learn how to use our currently available agents in a way that suppresses emergence of resistance and keeps these agents active for our patients. We plan to do this by 1) understanding the optimal way to dose Pseudomonas-active drugs in our hollow fiber infection model (HFIM) to suppress resistance and delineate the impact of different resistance mechanisms on this process 2) understand how to administer these drugs in combination in the HFIM to optimally suppress resistance emergence 3) validate the in vitro findings from the HFIM in a mouse model of Pseudomonas aeruginosa pneumonia.

描述（由申请人提供）：铜绿假单胞菌是ICU发病率和死亡率的主要原因，尤其是在呼吸机相关肺炎患者中。许多分离株具有多药耐药性，某些分离株对当前现有的抗感染剂具有抗性。目前，临床发育（人）中没有新的抗生素具有针对假单胞菌的新型作用机理。鉴于与新药物开发相关的周期时间，可能不会出现5至7年的抗生素具有新的病原体作用机理。因此，我们必须产生有关如何最好地抑制该病原体抗生素耐药性的新知识。这将有助于在我们等待新代理商的同时保存我们目前的药物。同样，当具有新的作用机制的代理商可用时，可以以最佳的方式抑制它们，无论是单一疗法还是结合使用。在此应用程序（特定目标＃1）中，我们假设我们可以通过在我们的空心纤维感染模型（HFIM）中研究这种病原体来鉴定最佳剂量和抑制抑制的给药时间表，并将大型数学模型拟合到HFIM数据以识别这些剂量和时间表。我们进一步假设不同的耐药机制将改变最佳剂量和时间表。我们建议研究野生型铜绿假单胞菌PAO-1分离株的同源性突变体，每个突变体都包含定义的耐药机制。这些发现将通过使用Monte Carlo Simulation（MCS）来桥接人。在特定的目标＃2中，我们建议检查组合化疗中的药物。我们开发了一个完全新颖的数学模型，可以描述两种药物组合化疗对铜绿假单胞菌分离株的影响。该模型是一个混合模型，允许该模型与代理的浓度时间疗程拟合，并将模型拟合到随着时间的推移而变化，这是由于存在易感性且易感性较低的生物体种群的结合而变化的。对该系统参数的强大识别将允许计算最佳组合方案以抑制阻力。如上所述，通过使用MC，将通过使用MC桥接该方案。 HFIM是一个体外系统。在特定的目标＃3中，我们还将在中性粒细胞减少小鼠肺炎模型中验证这些最佳和非最佳方案，并采用在AIMS＃1和2中研究的相同分离株。在研究这一点时，我们将对该方案使用“人性化”剂量，以便小鼠和人类药代动力学之间的差异不会推动不当推断。这将用于单疗和组合疗法。预期验证实验将进行设计和执行。结果将与体外发现进行比较，并与人桥接。因此，将针对抑制抗性突变体种群扩增的药物方案定义强大的原则。铜绿假单胞菌是重症监护病房中主要重要性的病原体，通常对我们治疗性武术中的许多药物具有抵抗力。由于没有具有独特作用机理对假单胞菌的独特作用机制，因此至少需要7年的时间，因此必须学习如何以抑制抵抗力的出现并使这些药物为患者保持活跃的方式使用我们当前可用的代理。我们计划通过1）理解在我们的空心纤维感染模型（HFIM）中理解剂量假单胞菌活性药物的最佳方法（HFIM），以抑制抵抗力并描述不同耐药机制对此过程的影响2）铜绿肺炎。