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Systems Toxicology Approach to Identifying Paracetamol Overdose

Paracetamol (acetaminophen (APAP)) is one of the most commonly used analgesics in the United Kingdom and the United States. However, exceeding the maximum recommended dose can cause serious liver injury and even death. Promising APAP toxicity biomarkers are thought to add value to those used current...

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Autores principales: Mason, Chantelle L., Leedale, Joseph, Tasoulis, Sotiris, Jarman, Ian, Antoine, Daniel J., Webb, Steven D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6027737/
https://www.ncbi.nlm.nih.gov/pubmed/29667370
http://dx.doi.org/10.1002/psp4.12298
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author Mason, Chantelle L.
Leedale, Joseph
Tasoulis, Sotiris
Jarman, Ian
Antoine, Daniel J.
Webb, Steven D.
author_facet Mason, Chantelle L.
Leedale, Joseph
Tasoulis, Sotiris
Jarman, Ian
Antoine, Daniel J.
Webb, Steven D.
author_sort Mason, Chantelle L.
collection PubMed
description Paracetamol (acetaminophen (APAP)) is one of the most commonly used analgesics in the United Kingdom and the United States. However, exceeding the maximum recommended dose can cause serious liver injury and even death. Promising APAP toxicity biomarkers are thought to add value to those used currently and clarification of the functional relationships between these biomarkers and liver injury would aid clinical implementation of an improved APAP toxicity identification framework. The framework currently used to define an APAP overdose is highly dependent upon time since ingestion and initial dose; information that is often highly unpredictable. A pharmacokinetic/pharmacodynamic (PK/PD) APAP model has been built in order to understand the relationships between a panel of biomarkers and APAP dose. Visualization and statistical tools have been used to predict initial APAP dose and time since administration. Additionally, logistic regression analysis has been applied to histology data to provide a prediction of the probability of liver injury.
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spelling pubmed-60277372018-07-06 Systems Toxicology Approach to Identifying Paracetamol Overdose Mason, Chantelle L. Leedale, Joseph Tasoulis, Sotiris Jarman, Ian Antoine, Daniel J. Webb, Steven D. CPT Pharmacometrics Syst Pharmacol Articles Paracetamol (acetaminophen (APAP)) is one of the most commonly used analgesics in the United Kingdom and the United States. However, exceeding the maximum recommended dose can cause serious liver injury and even death. Promising APAP toxicity biomarkers are thought to add value to those used currently and clarification of the functional relationships between these biomarkers and liver injury would aid clinical implementation of an improved APAP toxicity identification framework. The framework currently used to define an APAP overdose is highly dependent upon time since ingestion and initial dose; information that is often highly unpredictable. A pharmacokinetic/pharmacodynamic (PK/PD) APAP model has been built in order to understand the relationships between a panel of biomarkers and APAP dose. Visualization and statistical tools have been used to predict initial APAP dose and time since administration. Additionally, logistic regression analysis has been applied to histology data to provide a prediction of the probability of liver injury. John Wiley and Sons Inc. 2018-04-18 2018-06 /pmc/articles/PMC6027737/ /pubmed/29667370 http://dx.doi.org/10.1002/psp4.12298 Text en © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Mason, Chantelle L.
Leedale, Joseph
Tasoulis, Sotiris
Jarman, Ian
Antoine, Daniel J.
Webb, Steven D.
Systems Toxicology Approach to Identifying Paracetamol Overdose
title Systems Toxicology Approach to Identifying Paracetamol Overdose
title_full Systems Toxicology Approach to Identifying Paracetamol Overdose
title_fullStr Systems Toxicology Approach to Identifying Paracetamol Overdose
title_full_unstemmed Systems Toxicology Approach to Identifying Paracetamol Overdose
title_short Systems Toxicology Approach to Identifying Paracetamol Overdose
title_sort systems toxicology approach to identifying paracetamol overdose
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6027737/
https://www.ncbi.nlm.nih.gov/pubmed/29667370
http://dx.doi.org/10.1002/psp4.12298
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