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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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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. |
format | Online Article Text |
id | pubmed-6027737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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