AIMIn cases of paracetamol (acetaminophen, APAP) overdose, an accurate estimate of tissue-specific paracetamol pharmacokinetics (PK) and ingested dose can offer health care providers important information for the individualized treatment and follow-up of affected patients. Here a novel methodology is presented to make such estimates using a standard serum paracetamol measurement and a computational framework.
METHODSThe core component of the computational framework was a physiologically-based pharmacokinetic (PBPK) model developed and evaluated using an extensive set of human PK data. Bayesian inference was used for parameter and dose estimation, allowing the incorporation of inter-study variability, and facilitating the calculation of uncertainty in model outputs.
RESULTSSimulations of paracetamol time course concentrations in the blood were in close agreement with experimental data under a wide range of dosing conditions. Also, predictions of administered dose showed good agreement with a large collection of clinical and emergency setting PK data over a broad dose range. In addition to dose estimation, the platform was applied for the determination of optimal blood sampling times for dose reconstruction and quantitation of the potential role of paracetamol conjugate measurement on dose estimation.
CONCLUSIONSCurrent therapies for paracetamol overdose rely on a generic methodology involving the use of a clinical nomogram. By using the computational framework developed in this study, serum sample data, and the individual patient's anthropometric and physiological information, personalized serum and liver pharmacokinetic profiles and dose estimate could be generated to help inform an individualized overdose treatment and follow-up plan.
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Many of the pharmacokinetic measures used to characterize paracetamol overdoses were derived from therapeutic dosing studies.• Current assessment and treatment plans for paracetamol overdose cases generally rely on a generic methodology involving the use of a clinical nomogram.• Self-reported dose alone is a poor predictor of risk following paracetamol overdose, and lack of accurate knowledge of the ingested dose may hamper the effective long term management of these cases.
WHAT THIS STUDY ADDS• It provides a well-validated paracetamol PBPK model for humans under overdose conditions and a clinically-useful methodology for paracetamol dose estimation.• It elucidates the effect of blood sampling time and additional biomarker measurements on dose reconstruction.• It demonstrates a means to generate personalized serum and liver pharmacokinetic profiles and a dose estimate that should prove useful in developing an individualized overdose treatment and follow-up plan.