Biomarker-Guided Individualization of Antibiotic Therapy

被引:35
作者
Aulin, Linda B. S. [1 ]
de Lange, Dylan W. [2 ]
Saleh, Mohammed A. A. [1 ]
van der Graaf, Piet H. [1 ,3 ]
Voller, Swantje [1 ,4 ]
van Hasselt, J. G. Coen [1 ]
机构
[1] Leiden Univ, Leiden Acad Ctr Drug Res, Div Syst Biomed & Pharmacol, Leiden, Netherlands
[2] Univ Utrecht, Univ Med Ctr, Dept Intens Care Med, Utrecht, Netherlands
[3] Certara, Canterbury, Kent, England
[4] Leiden Univ, Leiden Acad Ctr Drug Res, Pharm, Leiden, Netherlands
关键词
C-REACTIVE PROTEIN; VENTILATOR-ASSOCIATED PNEUMONIA; MID-REGIONAL PROADRENOMEDULLIN; CRITICALLY-ILL PATIENTS; IMMUNE-RESPONSE; SEVERE SEPSIS; GLUTAMATE-DEHYDROGENASE; ELIMINATION RATE; RENAL-FUNCTION; EARLY MARKER;
D O I
10.1002/cpt.2194
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Treatment failure of antibiotic therapy due to insufficient efficacy or occurrence of toxicity is a major clinical challenge, and is expected to become even more urgent with the global rise of antibiotic resistance. Strategies to optimize treatment in individual patients are therefore of crucial importance. Currently, therapeutic drug monitoring plays an important role in optimizing antibiotic exposure to reduce treatment failure and toxicity. Biomarker-based strategies may be a powerful tool to further quantify and monitor antibiotic treatment response, and reduce variation in treatment response between patients. Host response biomarkers, such as CRP, procalcitonin, IL-6, and presepsin, could potentially carry significant information to be utilized for treatment individualization. To achieve this, the complex interactions among immune system, pathogen, drug, and biomarker need to be better understood and characterized. The purpose of this tutorial is to discuss the use and evidence of currently available biomarker-based approaches to inform antibiotic treatment. To this end, we also included a discussion on how treatment response biomarker data from preclinical, healthy volunteer, and patient-based studies can be further characterized using pharmacometric and system pharmacology based modeling approaches. As an illustrative example of how such modeling strategies can be used, we describe a case study in which we quantitatively characterize procalcitonin dynamics in relation to antibiotic treatments in patients with sepsis.
引用
收藏
页码:346 / 360
页数:15
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