Systems-based pharmacologic modelling to elucidate beta-lactam clinical pharmacodynamics and define optimal dosing regimens in severe pneumonia

基于系统的药理学模型阐明β-内酰胺临床药效学并确定重症肺炎的最佳给药方案

• 批准号: 10663370
• 负责人: Nathaniel James Rhodes
• 金额: $ 66.92万
• 依托单位: MIDWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-11 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10663370
• 关键词: Address; Affect; Alveolar; Antibiotic Resistance; Antibiotic Therapy; Antibiotics; Area Under Curve; Biological Assay; Bronchoalveolar Lavage Fluid; Cause of Death; Cefepime; Cessation of life; Classification; Clinical; Clinical Research; Clinical Treatment; Critical Illness; Data; Development; Diagnostic; Disease; Dose; Drug Exposure; Drug Kinetics; Epithelium; Failure; Funding; Goals; Health; Health Care Costs; Infection; Infrastructure; Intensive Care Units; Klebsiella aerogenes; Klebsiella oxytoca; Klebsiella pneumoniae; Knowledge; Liquid substance; Measures; Mechanical ventilation; Meropenem; Mission; Modeling; Nosocomial Infections; Nosocomial pneumonia; Organ; Outcome; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacodynamics; Phenotype; Piperacillin; Plasma; Pneumonia; Pseudomonas aeruginosa; Public Health; Regimen; Research; Research Infrastructure; Resistance; Risk; Risk Factors; Sampling; Site; Specimen; Statistical Models; System; Systems Biology; Time; Treatment Failure; United States National Institutes of Health; Universities; Validation; antibiotic resistant infections; beta-Lactams; biobank; clinical efficacy; clinical risk; combat; design; drug resistant pathogen; effective therapy; experience; falls; genome sequencing; high risk population; hospital analysis; improved; individual patient; mortality; mortality risk; participant enrollment; pathogen; pharmacodynamic model; pharmacokinetics and pharmacodynamics; pharmacologic; pneumonia treatment; prospective; response; sample collection; simulation; success; tool; treatment optimization; treatment strategy; whole genome

Project Abstract Hospital-acquired pneumonia (HAP) caused by antibiotic-resistant pathogens such as Klebsiella aerogenes, Klebsiella pneumoniae, and Pseudomonas aeruginosa are responsible treatment failure and mortality rates up to 50% and 30%, respectively. Beta-lactam antibiotics are a mainstay for the treatment of HAP, but antibiotic resistance continues to erode their clinical efficacy. Importantly, the efficacy of beta- lactams depends on achieving adequate pharmacokinetic-pharmacodynamic (PK/PD) exposures; however, many patients with HAP experience inadequate PK/PD because of changes in PK caused by critically illness. Precision Dosing strategies can overcome PK variability caused by critical illness, but Precision Dosing requires robust PK models and clinically validated PK/PD targets; such models and targets are currently lacking for patients with HAP. Without robust PK models and optimal PK/PD targets for antibiotic dosing, HAP patients will continue to experience high rates of treatment failure and death. Our proposal will adapt and extend the existing research infrastructure of the Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center to robustly address these gaps in knowledge. Our long-term goal is to develop Precision Dosing strategies that overcome PK variability caused by severe illness. The project objective is to utilize the infrastructure, samples, and data collected in SCRIPT to develop PK models in critically ill patients with HAP—thereby facilitating the development and validation of HAP-specific PK/PD models. Our central hypothesis is: (1) inadequate beta-lactam PK is common with standard “one-size-fits all” HAP dosing regimens; which (2) increases the risk of re- infection; that in turn (3) increases the likelihood of clinical treatment failure in HAP. In Aim 1, we will develop and evaluate PK models for use in Precision Dosing of beta-lactams for HAP. In Aim 2, we will evaluate the impact of alveolar beta-lactam PK/PD on outcomes in HAP including (a) treatment success and (b) pathogen reinfection. In Aim 3, we will identify patients who experience alveolar-plasma PK profile discordance—making plasma a poor surrogate for alveolar concentrations and placing these patients at risk of underdosing for pneumonia treatment—and determine clinical risk factors for such discordance. Our study will provide clinically validated tools which will facilitate the actualization of Precision Dosing for patients with HAP. Our study will have a positive clinical impact by providing optimal PK sampling times, generalizable PK models, HAP-specific PK/PD targets, and validated risk factors for alveolar- plasma PK discordance, all of which can be applied at the bedside for patients with HAP. This research is significant because it will provide the tools required to achieve Precision Dosing in HAP, which will advance the NIH mission to protect and improve the health of patients affected by resistant pathogens.

项目摘要