Development and Evaluation of CRRT-Specific Precision Dosing Models to Optimize Beta-Lactam Treatment for Patients with Hospital-Acquired Pneumonia
开发和评估 CRRT 特异性精确剂量模型,以优化医院获得性肺炎患者的 β-内酰胺治疗
基本信息
- 批准号:10740095
- 负责人:
- 金额:$ 26.54万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-06-23 至 2025-05-31
- 项目状态:未结题
- 来源:
- 关键词:Acute Renal Failure with Renal Papillary NecrosisAddressAlveolarAntibiotic ResistanceAntibiotic TherapyAntibioticsBronchoalveolar Lavage FluidCessation of lifeClinicalClinical ResearchCritical CareCritical IllnessDataDevelopmentDiagnosticDoseDrug KineticsEpitheliumEvaluationExperimental DesignsExploratory/Developmental GrantFocus GroupsFundingFutureGoalsHealthHealth Care CostsHospital MortalityInfectionInfrastructureInjury to KidneyIntensive Care UnitsKlebsiella aerogenesKlebsiella oxytocaKlebsiella pneumoniaeKnowledgeLiquid substanceLiteratureLungMeasuresMechanical ventilationMedicineMeropenemMissionModelingNosocomial InfectionsNosocomial pneumoniaOnline SystemsOutcomePathway interactionsPatientsPharmaceutical PreparationsPharmacodynamicsPlasmaPneumoniaPopulationPseudomonas aeruginosaPublic HealthQualifyingRandomized, Controlled TrialsRecommendationRegimenRenal Replacement TherapyResearchResearch InfrastructureRiskSamplingSchemeSiteStatistical ModelsSystems BiologyTranslatingTranslationsTreatment FailureUnited States National Institutes of HealthUniversitiesValidity and Reliabilityalveolar epitheliumantibiotic resistant infectionsassay developmentbeta-Lactamsbiobankclinical efficacyclinical riskdose individualizationdrug resistant pathogenexperiencehigh riskimprovedindividual patientinnovationmortalitymortality risknovelpathogenpharmacodynamic modelpneumonia treatmentpopulation basedpredictive modelingprospectiveresponsesample collectiontooltreatment optimization
项目摘要
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. Meropenem is a mainstay for the treatment of HAP, but
antibiotic resistance continues to erode its 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 models; such models for critically ill patients who develop kidney injury and require
continuous renal replacement therapy (CRRT) are currently lacking for HAP patients. Without Precision
Dosing models to help guide antibiotic dosing, these vulnerable patients will continue to experience high
rates of treatment failure and death. Whereas the status quo treatment of HAP patients requiring CRRT
uses population-based dosing schemes, our proposal will innovate Precision Dosing (i.e., individualized)
strategies for patients with HAP. We will leverage the infrastructure of the Successful Clinical Response In
Pneumonia Therapy (SCRIPT) Systems Biology Center to robustly address the unmet needs of patients
on CRRT. 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 Precision Dosing models for HAP. Our central hypothesis is: (1) CRRT leads to
variability in beta-lactam PK with standard “one-size-fits all” HAP dosing regimens which (2) increases the
risk of clinical treatment failure in HAP, (3) requiring Precision Dosing schemes. The rationale for our
study is that Precision Dosing is needed for CRRT patients with HAP and that these approaches must be
translated clinically. In Aim 1, we will develop and qualify Precision Dosing models for meropenem in
CRRT. In Aim 2, we will describe meropenem PK/PD target attainment in plasma and in the lung for
patients requiring CRRT. In Aim 3, we will create a web-based dosing calculator for translation to practice.
Our study will have a positive clinical impact by providing clinicians with the tools necessary to
ensure that each patient’s dosing is optimized. This research is significant because it addresses a critical
unmet need for optimized therapy. Upon completion, our study will have robustly characterized alveolar PK
in CRRT patients, filling a gap in the rigor of prior research. We will have translated our Precision Dosing
model predictions into actionable dosing regimens, which is innovative as no such calculators exist. Our
Precision Dosing calculator will be evaluated in a future R01-funded randomized controlled trial.
项目摘要
克雷伯菌等耐药病原体引起的医院获得性肺炎(HAP)
产气菌、肺炎克雷伯菌和铜绿假单胞菌是治疗失败的原因,
死亡率分别高达50%和30%。美罗培南是治疗HAP的主要药物,但
抗生素耐药性继续侵蚀其临床功效。重要的是,β-内酰胺类药物的疗效
依赖于实现足够的药代动力学-药效学(PK/PD)暴露;然而,许多
HAP患者由于危重疾病引起的PK变化而经历不充分的PK/PD。
精确给药策略可以克服危重疾病引起的PK变异性,
需要稳健的模型;这些模型适用于发生肾损伤并需要
目前HAP患者缺乏连续性肾脏替代治疗(CRRT)。无精度
给药模型,以帮助指导抗生素剂量,这些脆弱的患者将继续经历高
治疗失败率和死亡率。鉴于需要CRRT的HAP患者的治疗现状
使用基于人群的剂量方案,我们的建议将创新精确剂量(即,个性化)
HAP患者的治疗策略我们将利用成功临床反应的基础设施,
肺炎治疗(CNOT)系统生物学中心,以有力地解决患者未满足的需求
CRRT治疗。我们的长期目标是开发克服PK变异性的精确给药策略
由严重疾病引起的。该项目的目标是利用基础设施、样本和收集的数据
为HAP开发精确剂量模型。我们的中心假设是:(1)CRRT导致
标准“一刀切”HAP给药方案的β-内酰胺PK变异性,(2)增加了
HAP临床治疗失败的风险,(3)需要精确给药方案。我们的理由是,
一项研究表明,HAP CRRT患者需要精确给药,这些方法必须
临床翻译在目标1中,我们将开发并验证美罗培南的精确给药模型,
CRRT。在目标2中,我们将描述美罗培南在血浆和肺中的PK/PD目标达到情况,
需要CRRT的患者。在目标3中,我们将创建一个基于网络的剂量计算器,用于实践。
我们的研究将通过为临床医生提供必要的工具来产生积极的临床影响,
确保每个患者的剂量都得到优化。这项研究意义重大,因为它解决了一个关键问题,
优化治疗的需求未得到满足。完成后,我们的研究将具有稳健的肺泡PK特征
在CRRT患者中,填补了先前研究严谨性的空白。我们将把我们的精确剂量
将模型预测转化为可操作的给药方案,这是创新的,因为不存在这样的计算器。我们
将在未来的R 01资助的随机对照试验中评价精确剂量计算器。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nathaniel James Rhodes其他文献
Nathaniel James Rhodes的其他文献
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{{ truncateString('Nathaniel James Rhodes', 18)}}的其他基金
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 - 财政年份:2022
- 资助金额:
$ 26.54万 - 项目类别:
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