PII-090 - A PHARMACOKINETIC AND ENZYME TURNOVER MODEL PREDICTS MAJOR ROLES FOR CYP2B6 GENOTYPES ON THE MAGNITUDE OF EFAVIREZ AUTOINDUCTION OF METABOLISM AND CLEARNCE IN HEALTHY VOLUNTEERS

B. Aruldhas¹, M. Heathman², I. Metzger³, J. Lu⁴, B. Gufford², Z. Desta⁴; ¹Department of Pharmacology and Clinical Pharmacology, Christian Medical College, Vellore, Tamil Nadu, India, ²Indiana University, , United States, ³Universidade de Brasília, Brazil., , Universidade de Brasília, Brazil., ⁴Indiana University, Indianapolis, IN, USA.

Background: The antiretroviral drug efavirenz is primarily metabolized by the CYP2B6 enzyme and autoinduces its own metabolism, with large intersubject variability. This variability contributes to the wide variability in efavirenz pharmacokinetics, which determines clinical response and adverse effects. We tested the impact of CYP2B6 genotypes on efavirenz autoinduction, using a population pharmacokinetic-pharmacodynamic (PK-PD) modeling.

Methods: Plasma concentrations of efavirenz and its metabolites were quantified using LC/MS/MS method in 4594 samples collected from 135 healthy volunteers who received a single dose of efavirenz (600 mg PO) at baseline and after treatment with efavirenz (600 mg/day) for 17 days. CYP2B6 genotype and demographic information was obtained. The development, diagnostics, and validation of the PK-PD model was conducted using NONMEM, PsN, Pirana, and R software. The SAEM method and ADVAN 13 subroutine were employed for modeling.

Results: A two-compartment disposition model best-described efavirenz and its metabolites. The absorption process was most accurately captured using a sequential zero-order and first-order process. Interindividual variability (IIV) was incorporated into all PK parameters using an exponential relationship. Residual unexplained variability was well explained by a proportional error model. Following the validation of the single-dose drug and metabolites model with diagnostics including VPC, the multiple-dose model was developed. An enzyme turnover model was utilized to characterize the autoinduction of metabolism. The EC50 was estimated to be 2310 nM/L with a KOUT0 of 0.0389 hr-1. The shrinkage on IIV of EC50 and clearance were 21% and 9%, respectively. Graphical exploration of the covariates shows decreasing efavirenz clearance and autoinduction (increase in EC50) in poor metabolizer (PM) of CYP2B6 (Figure). Compared to normal metabolizer (NM), efavirenz clearance was reduced by 47% and 72% and EC50 for autoinduction was increased by 12% and 84% in intermediate metabolizer (IM) and PM of CYP2B6, respectively.

Conclusion: A population PK and turnover models were developed and show that the extent of efavirenz autoinduction and clearance is dependent on CYP2B6 genotype. Further modeling effort is ongoing to accurately quantify this autoinduction and its time course.