Pharmacokinetics of Efavirenz Dose Optimization in Pediatric Patients Using an in vitro–in vivo Extrapolation Model
Marco Siccardi1, L Almond2, S Khoo1, A Owen1, and D Back1
1Inst of Translational Med, Univ of Liverpool, UK and 2Simcyp Limited, Sheffield, UK
Background: Efavirenz (EFV) pharmacokinetics is characterized by marked inter-patient variability and a correlation between plasma exposure and efficacy has been described. The CYP2B6 516G>T polymorphism has been shown to affect plasma concentrations in adults and children. The aim of this study was to develop an in vitro–in vivo extrapolation (IVIVE) model to simulate EFV pharmacokinetics in a virtual pediatric population and explore dose adjustments based on the 516 G>T genotype.
Methods: Data in vitro describing the chemical properties, absorption, distribution, metabolism, and excretion (ADME) of EFV were used to simulate EFV pharmacokinetics at standard and alternative regimens in children <10 years old based on body weight using the Simcyp Simulator. Simulated pharmacokinetic parameters and the impact of 516G>T genotype were compared with published pediatric data.
Results: In a virtual Caucasian cohort of 100 children per weight band the simulated pharmacokinetic parameters were in good agreement with published data. Median clearance (CL/F/BSA) was 8.2 L/h/m2 (IQR, 4.7 to 14.4) vs 7.0 L/h/m2 (4.2 to 9.8) for 516 GG, 5.8 L/h/m2 (3.3 to 10.7) vs 5.7 L/h/m2 (4.5 to 6.9) for 516 GT and 3.8 L/h/m2 (2.3 to 6.2) vs 3.0 L/h/m2 (1.5 to 4.5) for 516 TT. The proportion of patients at standard and modified dosage with Cavg <1 mg/L (putative MEC) and above 4 mg/L (putative upper concentration for toxicity) are described in the table (data from standard regimens are shown in shade).
Conclusions: The IVIVE model predicts the pharmacokinetics of EFV in children with different CYP2B6 genotypes. Based on these findings, dose increments could be hypothesized for children with 516 GG, whereas patients with 516 TT could potentially benefit from a dose reduction. These simulations indicate that genotype-guided dose optimization could be used in pediatric patients and our model could form the basis of dose selection in prospective clinical trials.