4.6 Article

Biomarker-Guided Individualization of Antibiotic Therapy

Journal

CLINICAL PHARMACOLOGY & THERAPEUTICS
Volume 110, Issue 2, Pages 346-360

Publisher

WILEY
DOI: 10.1002/cpt.2194

Keywords

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Funding

  1. ZonMW ABR [541001007]

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Treatment failure of antibiotic therapy presents a major clinical challenge, necessitating optimization of individual patient treatment strategies. Biomarker-based approaches play a crucial role in guiding antibiotic treatment to reduce failure and toxicity, offering personalized treatment options and potential for further characterization through modeling approaches.
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.

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