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Biomarker‐Guided Individualization of Antibiotic Therapy

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 imp...

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Autores principales: Aulin, Linda B.S., de Lange, Dylan W., Saleh, Mohammed A.A., van der Graaf, Piet H., Völler, Swantje, van Hasselt, J.G. Coen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359228/
https://www.ncbi.nlm.nih.gov/pubmed/33559152
http://dx.doi.org/10.1002/cpt.2194
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author Aulin, Linda B.S.
de Lange, Dylan W.
Saleh, Mohammed A.A.
van der Graaf, Piet H.
Völler, Swantje
van Hasselt, J.G. Coen
author_facet Aulin, Linda B.S.
de Lange, Dylan W.
Saleh, Mohammed A.A.
van der Graaf, Piet H.
Völler, Swantje
van Hasselt, J.G. Coen
author_sort Aulin, Linda B.S.
collection PubMed
description 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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spelling pubmed-83592282021-08-17 Biomarker‐Guided Individualization of Antibiotic Therapy Aulin, Linda B.S. de Lange, Dylan W. Saleh, Mohammed A.A. van der Graaf, Piet H. Völler, Swantje van Hasselt, J.G. Coen Clin Pharmacol Ther Tutorials 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. John Wiley and Sons Inc. 2021-03-02 2021-08 /pmc/articles/PMC8359228/ /pubmed/33559152 http://dx.doi.org/10.1002/cpt.2194 Text en © 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Tutorials
Aulin, Linda B.S.
de Lange, Dylan W.
Saleh, Mohammed A.A.
van der Graaf, Piet H.
Völler, Swantje
van Hasselt, J.G. Coen
Biomarker‐Guided Individualization of Antibiotic Therapy
title Biomarker‐Guided Individualization of Antibiotic Therapy
title_full Biomarker‐Guided Individualization of Antibiotic Therapy
title_fullStr Biomarker‐Guided Individualization of Antibiotic Therapy
title_full_unstemmed Biomarker‐Guided Individualization of Antibiotic Therapy
title_short Biomarker‐Guided Individualization of Antibiotic Therapy
title_sort biomarker‐guided individualization of antibiotic therapy
topic Tutorials
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359228/
https://www.ncbi.nlm.nih.gov/pubmed/33559152
http://dx.doi.org/10.1002/cpt.2194
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