Pharmacodynamic modeling of antibiotics on cystic fibrosis P. aeruginosa biofilms

描述（由申请人提供）：关于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，使其能够在激烈的、反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是基于浮游生物（如液体）培养中生长的细菌的PD分析，不能推断为生物膜。此外，已知不同种类的抗生素针对生物膜内不同的亚群。本研究的长期目标是通过PD对细菌生物膜的应用，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研究基于简单的“活”或“死”计数来量化抗菌效果。本研究提出的独特的时空PD建模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及其对耐药性进化的相关影响。Aim 1的目标是优化设计一个创新的动态体外生物膜PK/PD模型，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-时间分布。在Aim 2中，该模型将用于确定美罗培南和tobramycin的生物膜PD靶标，单独或联合使用，在一组独特的基因相同的铜绿假单胞菌分离株上，从CF患者身上纵向收集了35年，从而允许比较引起早期与晚期疾病以及急性与慢性感染的分离株的PD靶标。在Aim 3中，描述抗生素活性和生物膜杀死之间关系的数学模型将被开发。我们组建了一支国际、多学科的研究团队，在PK/PD、微生物生物膜、CF和数学建模方面具有专业知识。这项研究的结果将用于研究新的抗生素方案，以最大限度地杀死生物膜。这项转化性研究将为抗菌PD的研究提供一个创新的新框架，该框架解释了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，并将有助于发现特异性针对CF中铜绿假单胞菌生物膜的替代抗菌剂量策略和药物组合，最终目标是改善临床护理。本研究结果将广泛应用于其他生物膜形成生物（如金黄色葡萄球菌），它们是人类感染的重要原因，如心内膜炎、骨科植入物感染和导管相关感染。

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. PUBLIC HEALTH RELEVANCE: The proposed research is relevant to public health because bacterial biofilms make up over 80% of important human infections, including cystic fibrosis, yet current in vitro pharmacodynamic models used for antibiotic dose optimization do not account for the role of biofilms in antimicrobial resistance. Current guidelines for antimicrobial treatmen of P. aeruginosa lung infection in cystic fibrosis can only suppress infection and not cure. Systematic pharmacodynamic profiling of antibiotics on P. aeruginosa biofilms may lead to antibiotic dosing regimens directed towards the biofilm and improve clinical outcomes in patients with cystic fibrosis.