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Use of a physiologically-based pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz.

Siccardi M, Olagunju A, Seden K, Ebrahimjee F, Rannard S, Back D, Owen A - In Silico Pharmacol (2013)

Bottom Line: Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.

ABSTRACT

Purpose: 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.

No MeSH data available.


Related in: MedlinePlus

Simulated artemether concentration-time profile for a dose of 80 mg twice daily with and without efavirenz. The full black line represents the mean (± SE) simulated concentrations and grey lines represent data observed in a clinical study (Byakika-Kibwika et al. 2012).
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Fig2: Simulated artemether concentration-time profile for a dose of 80 mg twice daily with and without efavirenz. The full black line represents the mean (± SE) simulated concentrations and grey lines represent data observed in a clinical study (Byakika-Kibwika et al. 2012).

Mentions: Simulated pharmacokinetics of artemether and efavirenz were in good accordance with previously described clinical data, as represented in Table 3 and Figure 2 (Byakika-Kibwika et al. 2012; Huang et al. 2012). In a virtual cohort of 50 patients treated with 80 mg of artemether twice daily for three days the simulated median (range) AUC was equal to 166 (55–678) vs 119 (26–917) ng/ml•h (reference value), Cmax 30 (11–73) vs 29 (10–247) ng/ml. Simulation of artemether drug disposition was characterised by low bioavalability (Foral = 0.11), with around 14% of the dose not absorbed (Fa = 0.86), high intestinal metabolism (Fg = 0.21) and high first pass metabolism (Fh = 0.60). High apparent volume of distribution (V/F = 1640 L) was predicted, in accordance to clinical studies. Systemic metabolism mediated by CYP2B6 and CYP3A4 was characterised by a high CL/F of 268 L/h.Figure 2


Use of a physiologically-based pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz.

Siccardi M, Olagunju A, Seden K, Ebrahimjee F, Rannard S, Back D, Owen A - In Silico Pharmacol (2013)

Simulated artemether concentration-time profile for a dose of 80 mg twice daily with and without efavirenz. The full black line represents the mean (± SE) simulated concentrations and grey lines represent data observed in a clinical study (Byakika-Kibwika et al. 2012).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230487&req=5

Fig2: Simulated artemether concentration-time profile for a dose of 80 mg twice daily with and without efavirenz. The full black line represents the mean (± SE) simulated concentrations and grey lines represent data observed in a clinical study (Byakika-Kibwika et al. 2012).
Mentions: Simulated pharmacokinetics of artemether and efavirenz were in good accordance with previously described clinical data, as represented in Table 3 and Figure 2 (Byakika-Kibwika et al. 2012; Huang et al. 2012). In a virtual cohort of 50 patients treated with 80 mg of artemether twice daily for three days the simulated median (range) AUC was equal to 166 (55–678) vs 119 (26–917) ng/ml•h (reference value), Cmax 30 (11–73) vs 29 (10–247) ng/ml. Simulation of artemether drug disposition was characterised by low bioavalability (Foral = 0.11), with around 14% of the dose not absorbed (Fa = 0.86), high intestinal metabolism (Fg = 0.21) and high first pass metabolism (Fh = 0.60). High apparent volume of distribution (V/F = 1640 L) was predicted, in accordance to clinical studies. Systemic metabolism mediated by CYP2B6 and CYP3A4 was characterised by a high CL/F of 268 L/h.Figure 2

Bottom Line: Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK.

ABSTRACT

Purpose: 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.

No MeSH data available.


Related in: MedlinePlus