Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms

抗生素对囊性纤维化铜绿假单胞菌生物膜的药效学模型

• 批准号: 8649011
• 负责人: Katherine Y. Yang
• 金额: $ 38.86万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-22 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8649011
• 关键词: Accounting; Acute; Acute Disease; Adult; Algorithms; Aminoglycosides; Anti-Bacterial Agents; Antibiotic Resistance; Antibiotic Therapy; Antibiotics; Antimicrobial Effect; Antimicrobial Resistance; Bacteria; Biomass; California; Cause of Death; Cells; Chronic; Clinical; Clinical Pharmacists; Collaborations; Collection; Combined Antibiotics; Cystic Fibrosis; Data; Denmark; Development; Disease; Dose; Drug Combinations; Drug Kinetics; Drug usage; Endocarditis; Evolution; Exhibits; Film; Genetic; Genus staphylococcus; Goals; Growth; Guidelines; Heterogeneity; Host Defense; Human; Imagery; Implant; In Vitro; Infection; International; Intravenous; Investigation; Lactams; Lead; Life; Liquid substance; Lung; Mediating; Meropenem; Metabolic; Microbial Biofilms; Modeling; Multi-Drug Resistance; Organism; Orthopedics; Outcome; Patients; Pharmacodynamics; Predisposition; Pseudomonas aeruginosa; Public Health; Regimen; Research; Research Methodology; Resistance; Respiratory Failure; Role; Sampling; San Francisco; Schedule; Serum; Simulate; Staging; Structure; System; Testing; Time; Tobramycin; Training; Translational Research; Treatment outcome; United States National Institutes of Health; Universities; Yang; antimicrobial; base; catheter related infection; clinical care; cystic fibrosis patients; design; drug development; effective therapy; experience; flexibility; improved; in vitro Model; in vivo; innovation; killings; mathematical model; multidisciplinary; novel strategies; pathogen; pharmacodynamic model; pharmacokinetic model; pressure; response; time use; translational study

DESCRIPTION (provided by applicant): Little is known regarding the pharmacokinetics (PK) and pharmacodynamics (PD) of antibiotics and biofilms yet bacterial biofilms account for over 80% of all important human infections, including cystic fibrosis (CF). The development of effective therapies to counter biofilm infections has been called one of the most pressing challenges in anti-bacterial drug development by the NIH. P. aeruginosa undergoes extensive genetic adaptation in the CF lung over time, allowing it to persist despite intense, repeated courses of antimicrobial treatment. Thus the current goal of antimicrobial therapy is to suppress infection and not cure. Guidelines for the treatment of P. aeruginosa airway infection are based upon PD analyses of bacteria grown in planktonic (e.g. liquid) culture which cannot be extrapolated to biofilms. Additionally, different classes of antibiotics are known to target differnt subpopulations within the biofilm. The long-term goal of this study is to identify the antibiotic combinations, doses, and schedules needed to eradicate P. aeruginosa biofilms in patients with CF through the application of PD on bacterial biofilms. Traditional PK/PD studies quantify antimicrobial effect based upon simple counts of "live" or "dead." The unique spatial and temporal approach to PD modeling proposed in this study will allow simultaneous visualization and quantification of the exposure response relationship of antibiotics on heterogeneous subpopulations within the biofilm in real-time and the associated effect on resistance evolution. The goal of Aim 1 is to optimize the design of an innovative dynamic in vitro biofilm PK/PD model that can simulate in vivo antibiotic concentration-time profiles on P. aeruginosa biofilms under continuous culture conditions. In Aim 2, this model will be used to determine the biofilm PD targets of meropenem and tobramycin, administered alone and in combination, on a unique collection of genetically identical P. aeruginosa isolates longitudinally-collected from CF patient over a period of 35 years thus allowing for comparisons in PD targets between isolates causing early vs. late disease and acute vs. chronic infection. In Aim 3, mathematical models describing the relationship between antibiotic activity and biofilm killing will be developed. We have assembled an international, multi-disciplinary research team with expertise in PK/PD, microbial biofilms, CF, and mathematical modeling. Results from this study will be used to investigate new antibiotic regimens for maximal bio- film killing. This translational study will provide an innovatve new framework for the investigation of antimicrobial PD that accounts for the genetic adaptations and phenotypic diversity observed in P. aeruginosa biofilms and will enable the discovery of alternative antimicrobial dosing strategies and drug combinations specifically targeting P. aeruginosa biofilms in CF with the ultimate goal of improving clinical care. Results of this study will have broad applications toward other biofilm-forming organisms (e.g., Staphyloccocus aureus) which are important causes of human infections such as endocarditis, orthopedic-implant infections, and catheter-related infections.

描述（由申请人提供）：人们对抗生素和生物膜的药代动力学 (PK) 和药效学 (PD) 知之甚少，但细菌生物膜占所有重要人类感染的 80% 以上，包括囊性纤维化 (CF)。开发对抗生物膜感染的有效疗法被美国国立卫生研究院称为抗菌药物开发中最紧迫的挑战之一。随着时间的推移，铜绿假单胞菌在 CF 肺中经历了广泛的遗传适应，使其能够在密集、重复的抗菌治疗过程中持续存在。因此，目前抗菌治疗的目标是抑制感染而不是治愈。铜绿假单胞菌气道感染的治疗指南基于对浮游（例如液体）培养物中生长的细菌的 PD 分析，该分析不能外推至生物膜。此外，已知不同类别的抗生素针对生物膜内的不同亚群。本研究的长期目标是通过对细菌生物膜应用 PD 来确定根除 CF 患者铜绿假单胞菌生物膜所需的抗生素组合、剂量和时间表。传统的 PK/PD 研究根据简单的“活”或“死”计数来量化抗菌效果。本研究中提出的独特的 PD 建模空间和时间方法将允许实时可视化和量化抗生素对生物膜内异质亚群的暴露反应关系以及对耐药性进化的相关影响。目标 1 的目标是优化创新动态体外生物膜 PK/PD 模型的设计，该模型可以模拟连续培养条件下铜绿假单胞菌生物膜上的体内抗生素浓度-时间曲线。在目标 2 中，该模型将用于确定美罗培南和妥布霉素的生物膜 PD 靶点，单独或联合给药，对从 CF 患者体内纵向收集的 35 年期间的独特的遗传相同的铜绿假单胞菌分离物进行收集，从而允许对引起早期与晚期疾病以及急性与慢性感染的分离株之间的 PD 目标进行比较。在目标 3 中，将开发描述抗生素活性和生物膜杀灭之间关系的数学模型。我们组建了一支国际化、多学科的研究团队，拥有 PK/PD、微生物生物膜、CF 和数学建模方面的专业知识。这项研究的结果将用于研究新的抗生素治疗方案，以最大限度地杀死生物膜。这项转化研究将为抗菌 PD 的研究提供一个创新的新框架，解释铜绿假单胞菌生物膜中观察到的遗传适应性和表型多样性，并将有助于发现专门针对铜绿假单胞菌生物膜的替代抗菌剂量策略和药物组合。 CF 的最终目标是改善临床护理。这项研究的结果将广泛应用于其他生物膜形成生物体（例如金黄色葡萄球菌），这些生物膜形成生物体是人类感染（例如心内膜炎、骨科植入物感染和导管相关感染）的重要原因。