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A systems toxicology paracetamol overdose framework: accounting for high-risk individuals

Mason, CL, Leedale, J, Tasoulis, S, Jarman, I and Webb, SD (2019) A systems toxicology paracetamol overdose framework: accounting for high-risk individuals. Computational Toxicology, 12. ISSN 2468-1113

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The most commonly prescribed painkiller worldwide, paracetamol (acetaminophen, APAP) is also the predominant cause of acute liver failure (ALF), and therefore paracetamol-induced liver toxicity remains an important clinical problem. The standard clinical treatment framework for paracetamol overdose currently allows for antidote therapy decisions to be made based on a nomogram treatment line. This treatment threshold is lowered for patients adjudged to be highly susceptible to liver injury due to risk factors such as anorexia nervosa or bulimia. Additionally, both the original and adjusted clinical frameworks are highly dependent on knowledge from the patient regarding time since ingestion and initial dose amount, both of which are often highly unpredictable. We have recently developed a pre-clinical framework for predicting time since ingestion, initial dose amount and subsequent probability of liver injury based on novel biomarker concentrations. Here, we use identifiability analysis as a tool to increase confidence in our model parameter estimates and extend the framework to make predictions for both healthy and high-risk populations. Through pharmacokinetic-pharmacodynamic model refinement, we identify thresholds that determine whether necrosis or apoptosis is the dominant form of cell death, which can be essential for effective ALF interventions. Using a single blood test, rather than the multiple tests required in the current clinical frameworks, our model provides overdose identification information applicable for healthy and high-risk individuals as well as quantitative measures of estimated liver injury probability.

Item Type: Article
Subjects: H Social Sciences > HA Statistics
R Medicine > R Medicine (General)
R Medicine > RA Public aspects of medicine > RA1190 Toxicology. Poisions
Divisions: Applied Mathematics (merged with Comp Sci 10 Aug 20)
Publisher: Elsevier
Date Deposited: 27 Sep 2019 10:46
Last Modified: 04 Sep 2021 08:50
DOI or ID number: 10.1016/j.comtox.2019.100103
URI: https://researchonline.ljmu.ac.uk/id/eprint/11392
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