title: Use of a physiologically-based pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz.
abstract: OBJECTIVE
  To treat malaria, HIV-infected patients normally receive artemether (80 mg twice daily) concurrently with antiretroviral therapy and drug-drug interactions can potentially occur. Artemether is a substrate of CYP3A4 and CYP2B6, antiretrovirals such as efavirenz induce these enzymes and have the potential to reduce artemether pharmacokinetic exposure. The aim of this study was to develop an in vitro in vivo extrapolation (IVIVE) approach to model the interaction between efavirenz and artemether. Artemether dose adjustments were then simulated in order to predict optimal dosing in co-infected patients and inform future interaction study design.
  
  
  METHODS
  In vitro data describing the chemical properties, absorption, distribution, metabolism and elimination of efavirenz and artemether were obtained from published literature and included in a physiologically based pharmacokinetic model (PBPK) to predict drug disposition simulating virtual clinical trials. Administration of efavirenz and artemether, alone or in combination, were simulated to mirror previous clinical studies and facilitate validation of the model and realistic interpretation of the simulation. Efavirenz (600 mg once daily) was administered to 50 virtual subjects for 14 days. This was followed by concomitant administration of artemether (80 mg eight hourly) for the first two doses and 80 mg (twice daily) for another two days.
  
  
  RESULTS
  Simulated pharmacokinetics and the drug-drug interaction were in concordance with available clinical data. Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%. Dose increases of artemether, to correct for the interaction, were simulated and a dose of 240 mg was predicted to be sufficient to overcome the interaction and allow therapeutic plasma concentrations of artemether.
  
  
  CONCLUSIONS
  The model presented here provides a rational platform to inform the design for a clinical drug interaction study that may save time and resource while the optimal dose is determined empirically. Wider application of IVIVE could help researchers gain a better understanding of the molecular mechanisms underpinning variability in drug disposition.
authors.affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
authors.forename: Marco
authors.initials: M
authors.lastname: Siccardi
authors.affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK ; Faculty of Pharmacy, Obafemi Awolowo University, Ile-Ife, Nigeria.
authors.forename: Adeniyi
authors.initials: A
authors.lastname: Olagunju
authors.affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
authors.forename: Kay
authors.initials: K
authors.lastname: Seden
authors.affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
authors.forename: Farid
authors.initials: F
authors.lastname: Ebrahimjee
authors.affiliation: Department of Chemistry, University of Liverpool, Liverpool, UK.
authors.forename: Steve
authors.initials: S
authors.lastname: Rannard
authors.affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
authors.forename: David
authors.initials: D
authors.lastname: Back
authors.affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Owen
keywords: Artemether; Drug interaction; Efavirenz; IVIVE; Pharmacokinetics; Simulation