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dc.creatorMason C.L., Leedale J., Tasoulis S., Jarman I., Webb S.D.en
dc.date.accessioned2023-01-31T08:57:52Z
dc.date.available2023-01-31T08:57:52Z
dc.date.issued2019
dc.identifier10.1016/j.comtox.2019.100103
dc.identifier.issn24681113
dc.identifier.urihttp://hdl.handle.net/11615/76408
dc.description.abstractThe 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. © 2019 Elsevier B.V.en
dc.language.isoenen
dc.sourceComputational Toxicologyen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85070783096&doi=10.1016%2fj.comtox.2019.100103&partnerID=40&md5=fd6670dd82550a04751e391d4d525e24
dc.subjectBiomarkersen
dc.subjectCell deathen
dc.subjectDiseasesen
dc.subjectPatient treatmenten
dc.subjectRisk assessmenten
dc.subjectRisk perceptionen
dc.subjectAcute liver failureen
dc.subjectAPAPen
dc.subjectDILIen
dc.subjectHigh-risk individualsen
dc.subjectIdentifiabilityen
dc.subjectIn-silicoen
dc.subjectLiver injuriesen
dc.subjectLiver toxicityen
dc.subjectParacetamolen
dc.subjectSystems toxicologiesen
dc.subjectPharmacokineticsen
dc.subjectalanine aminotransferaseen
dc.subjectcytokeratin 18en
dc.subjectglutathioneen
dc.subjecthigh mobility group B1 proteinen
dc.subjectn acetyl 1,4 benzoquinone imineen
dc.subjectparacetamolen
dc.subjectacute liver failureen
dc.subjectanimal experimenten
dc.subjectanimal modelen
dc.subjectapoptosisen
dc.subjectArticleen
dc.subjectblood analysisen
dc.subjectcell deathen
dc.subjectclinical assessmenten
dc.subjectclinical effectivenessen
dc.subjectconceptual frameworken
dc.subjectcontrolled studyen
dc.subjectdrug intoxicationen
dc.subjectdrug overdoseen
dc.subjecthigh risk populationen
dc.subjecthumanen
dc.subjectingestionen
dc.subjectmathematical modelen
dc.subjectmouseen
dc.subjectnonhumanen
dc.subjectpatient attitudeen
dc.subjectpharmacodynamicsen
dc.subjectpharmacokinetic parametersen
dc.subjectrisk assessmenten
dc.subjectrisk factoren
dc.subjecttime to treatmenten
dc.subjecttissue necrosisen
dc.subjectElsevier B.V.en
dc.titleA systems toxicology paracetamol overdose framework: accounting for high-risk individualsen
dc.typejournalArticleen


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