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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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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. |
format | Online Article Text |
id | pubmed-8359228 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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