Open Science Repository Pharmaceutics
Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population
Jackson K. Mukonzo [1, 2]
 Department of Pharmacology & Therapeutics, Makerere University College of Health Sciences, Uganda
 The CTN, CIHR Canadian HIV Trials Network
Efavirenz is the currently recommended first choice NNRTI for HIV patients receiving rifampicin TB co-treatment. While efavirenz exhibits a narrow therapeutic window, with plasma drug > 4 µg/ml and < 1 µg/ml being associated with central nervous system symptoms and increased virological failure respectively, it also exhibits significant inter-individual pharmacokinetic and pharmacodynamic variability.
Africans, a population that is uniquely different in terms of frequency of SNPs relevant for efavirenz pharmacokinetics and treatment outcome is also most affected by both HIV and TB, therefore requiring rifampicin-efavirenz co-treatment. Genes known to predict efavirenz pharmacokinetics include CYP2B6 and ABCB1. Rifampicin is an enzyme inducer for CYP2B6. While CYPB6 SNP frequencies differ greatly for Africans compared to other populations, efavirenz dosing has not been optimized for the population. We aim to use pharmacokinetic-pharmacogenetic–pharmacodynamic modeling in NONMEM to predict efavirenz optimal doses for Uganda patients.
Keywords: efavirenz, dosing, African, HIV patients.
Citation: Mukonzo, J. K. (2013). Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population. Open Science Repository Pharmaceutics, Online(open-access), e70081939. doi:10.7392/Pharmaceutics.70081939
Received: February 11, 2013
Published: March 11, 2013
Copyright: © 2013 Mukonzo, J. K. Creative Commons Attribution 3.0 Unported License.
Tuberculosis (TB) remains the most frequently encountered
co-morbidity among HIV infected patients particularly in sub-Saharan
Africa. Currently rifamycins constitute a cornerstone of anti-TB
therapy. Use of rifamycins in patients co-treated with antiretroviral
therapy (ART) is marred with drug-drug interactions
induction of the activity of the CYP enzymes and the transporter
Among the rifamycins, rifampicin exhibits
greatest effect on activity of both CYP enzymes and P-gp.
Non-availability of rifabutin in low resource countries is a
limitation for both ART and anti-TB treatment options during the
scourge of the two pandemics.
Efavirenz is currently the recommended first choice Non-Nucleoside
Reverse Transcriptase Inhibitors (NNRTIs) for
particularly during co-treatment with rifampicin. Efavirenz, however,
exhibits a narrow therapeutic window, as plasma drug > 4 µg/ml
have been associated with more central nervous system (CNS) toxicity
while the rate of virologic failure increases with concentration <
1 µg/ml . Inter-patient variations in efavirenz hepatic
metabolism and P-gp mediated movement across plasma membranes are
some of the main causes of inter-individual variations in the plasma
concentration of the drug. Efavirenz undergoes oxidative
hydroxylation primarily by CYP2B6 to 8-hydroxyefavirenz, which is its
major metabolite, and to 7-hydroxyefavirenz as a minor metabolite .
CYP2B6 (516 G→T and c.136A→G)
polymorphisms have been associated with differences in efavirenz
plasma exposure and CNS toxicities in most populations suggesting
that prescription of lower efavirenz doses could be warranted in
subjects harboring the T/T genotype in order to minimize side effects
without compromising the efficacy of the drug.
Although there are
conflicting reports on whether efavirenz is a substrate for P-gp,
lower efavirenz plasma levels, better immune recovery in Caucasians
who carried the 3435T/T genotype and lack of EFV resistance have been
associated with polymorphisms in the ABCB1 gene , while ABCB1
c.4036 A→G influence both efavirenz plasma and intracellular
Rifampicin induces expression and activity of CYP2B6 leading to 22 –
26% reduction of
efavirenz plasma exposure . The
increase in CYP2B6 activity due to rifampicin varies widely from 2.5
to 13-fold . Additionally, variability in efavirenz concentrations is
greater in the presence of rifampicin than without rifampicin, a
probable manifestation of inherent differences in the inducibility of
variants. Inter-individual differences in clearance of
efavirenz during co-administered with rifampicin complicates
decisions about efavirenz dose adjustment in settings of concurrent
rifampicin-containing TB therapy .
Africans, a population that is uniquely different in terms of
frequency of SNPs relevant for efavirenz pharmacokinetics and
treatment outcomes, are also most affected by both HIV and TB,
therefore requiring rifampicin-efavirenz co-treatment. The lack of
efavirenz dose optimization may lead to clusters of African patients
exhibition of sub or supra therapeutic efavirenz concentrations,
leading to viral resistance or intolerable toxicities respectively.
We aim to optimize efavirenz HIV treatment outcomes among Africans
using pharmacokinetic-pharmacogenetic–pharmacodynamic modeling
in NONMEM. Model predictions of drug concentrations, associated
virologic decay and immunologic recovery rates will be compared to
provide efavirenz dosing recommendations for
Ugandan HIV patients with and without TB co-treatment as well as the
different CYP2B6 genotype clusters determined
Materials and methods
This study will utilize data that was collected from a recently
completed clinical study for which a total 105 healthy volunteersand
263 patients ART naïve HIV patients, with (n =157) or without
concomitant TB (n=106), attending Mulago and Butabika National
referral and Bwera hospitals in Uganda, recruited during 2008 to
Study area and population
Study participant recruitment was conducted in three districts
including two urban districts (Kampala and Mukono) and one rural
district (Kasese). Kampala and Mukono districts are located in
central Uganda. The population in Kampala and Mukono districts is
estimated at 3.0 and 1.07 million people respectively and is largely
drawn from the various rural parts of Uganda, bringing all tribes
Kasese district is, on the other hand, located in the
western part of the country bordering with the Democratic Republic of
Congo. The district population that is estimated at 660,000 people is
largely of the Konjo tribe.
Adult healthy volunteers(n=105), confirmed by clinical examination,
renal and liver function tests, HIV and hepatitis B serology, were
treated with single dose efavirenz (600mg) before intensive blood
sampling of 0-72 hours was performed. Health volunteer participants
were genotyped for 30 SNPs in the CYP2B6, CYP3A5 and ABCB1.
genotyped for included CYP2B6 (*6 and *11), CYP3A5 (*3,*6 and*7) and
ABCB1 (rs3842 and 3435C>T).
HIV/AIDS ART naïve patients were
recruited at the HIV clinics at Butabika National referral hospitals
in Kampala (n= 60) and Bwera Hospital, Kasese (n= 47). TB co-infected
HIV patient’s (n= 152) naïve to both ART and anti-TB
therapy were recruited from the TB-HIV clinic at Mulago National
Referral Hospital. All patients were treated for HIV with efavirenz
600mg daily doses in combination with zidovudine and lamivudine.
Follow up period was 32 weeks. Patients co-infected with TB received
rifampicin based anti-TB regimen for 6 month (2EHRZ/4HR) in addition
to ART. CD4 analysis was performed to ensure eligibility for HIV
All patient participants were genotyped for CYP2B6 (*6
and *11), CYP3A5 (*3,*6 and *7) and ABCB1 (rs 3842 and 3435C>T).
Mid-dose plasma efavirenz concentrations samples were drawn on days 1
and 3 then weeks 1, 2, 4, 6, 8, 12, 16, 20, 24, 28 and 32. Twenty
nine of the patients were intensively sampled within 24 hours of
treatment initiation and compared with healthy volunteers. Patients
were also evaluated for adverse events including neuropsychotic ones
(sleep disorders, hallucinations and cognition impairment).
determination of efavirenz
Plasma was prepared from blood samples by centrifugation at 3000 g
for 10 min and stored at -70°C until high performance liquid
chromatography (HPLC) analysis was performed. Plasma efavirenz was
determined by reverse-phase with ultraviolet (UV) detection. The HPLC
machine, Agilent series 1100, consisting of column compartment
G1316A, Degasser G132A, Quat pump G1311A, an auto-sampler ALS,
G1329A, and G1315B diode array detector was used. The mobile phase
consisted of 30% acetonitrile, 30% methanol, 4 mmol l-1
potassium hydroxide and 10 mmol l-1
acetic acid (pH 4.3).
Plasma proteins were precipitated with acetonitrile before
centrifuging. Elution was performed at 0.80 ml min-1 for 3.5 min. The
retention time for efavirenz was 2.42 min as detected at UV-VIS 1,
210 nm, UV-VIS 2,220 nm. The method was linear, with a within-day
coefficient of variation of 3.2, 3.3 and 5.1% at concentrations of
2.0 mM (n
= 17), 8.0 mM (n
= 17), and 20 mM (n
16), respectively, and a between-day coefficient of variation of 4.1%
= 50). The limit of quantification for the method was set
at 0.35 mM.
Fragment Length PCR (RFLP)
RFLP was used to genotype for C3435T, C1236T and G(A)2677T in the
ABCB1 gene according to Tang et al
and Cascorbi et al
PCRs were performed in a reaction mixture (25 ml) containing buffer
X10, 0.125 ml Smart Taq hot DNA polymerase, 1.6–2.0 ml MgCl2
(25 mM l-1), 6.25 mM dNTPs and primers. Endonucleases Bsp1431,
Eco01091 (Drall) and BshNi(HgiCl) were used to digest PCR products
for C3435T, C1236T and G(A)2677T, respectively, followed by gel
Genomic DNA was isolated using QIAgen kit and genotyped for
the three genes: CYP2B6, CYP3A5 and ABCB1 by minisequencing using
micro-tag arrays method. Cyclic minisequencing reactions with
fluorescently labeled dideoxynucleotides were performed using
multiplex polymerase chain reaction (PCR) product as template and
detection primers, designed to anneal immediately adjacent to and
upstream of the SNP site. Primer sequences are available upon
request. The microarrays were prepared using detection primers
carrying unique 5′ tag sequences and oligonucleotides
complementary to the tag sequence of the minisequencing primers,
immobilized on a microarray. Hybridization was performed as according
Lindroos et al
and Lovmar et al
. The QuantArray file
was exported and analysed using the SNPSnapper analysis software,
version 4.0 beta.
Allelic discrimination reactions were performed
(Applied Biosystems, CA, USA) genotyping
assays: (C___7586657_20 for ABCB1
3435C>T, C___7817765_60 for
C__29560333_20 for CYPB6
] for CYP2B6
C__26201809_30 for CYP3A5
C__30203950_10 for CYP3A5
]) and C__32287188_10
on ABI 7500 FAST
(Applied Biosystems, Foster City, CA).
The final volume for each reaction was 10 μl, consisting of 2x
TaqMan Universal PCR Master Mix (Applied
Biosystems), 20 X drug metabolising genotype assay mix and 10 ng
genomic DNA. The PCR profile consisted of an initial step at 50o
for 2 min and 50 cycles with 95o
for 10 minutes and 92o
for 15 sec.
Data, including efavirenz pharmacokinetic data, pharmacogenetic data
(CYP2B6 (*6 and *11),
pharmacodynamic data (CD4 T-cell counts, viral load, liver, renal and
CNS profiles) and demographic profiles collected from healthy
volunteers, TB/ HIV or HIV alone patients will be pooled together
before performing population pharmacokinetic/pharmacodynamic modeling
to predict optimal efavirenz doses during and without TB co-treatment
and for individual CYP2B6 genotypes.
Data modeling will be performed
using first order conditional estimation with interaction (FOCE-I) in
NONMEM 7. Model discrimination will be based on relative objective
function values (OFV), precision of parameter estimates and
goodness-of-fit plots, including a visual predictive check.
From existing literature, a two compartment model will be applied in
the current project.
Clearance and volume related parameters will be
scaled allometrically by body weight and centered to the median body
weight (Eq. 1).
being the individual parameter estimate and Ppop
the parameter estimate for a patient with median body weight.
scaling factor will be set a priori to ¾ for clearances (i.e.,
Cl and Q) and to 1 for volumes of distribution.
A variety of
absorption models will be tested in the model development process,
including: 1) a single first-order process, 2) sequential first-order
processes, 3) a sequential zero-order followed by first-order
process, and 4) a transit absorption model where the number of
theoretical absorption compartments (NT) and the transit rate
) are estimated.
administration, autoinduction of efavirenz clearance occurs to
different degrees depending upon the CYP2B6 genotype.
induction in clearance will be modeled as a time-dependent change in
from a pre-induced clearance (Clpre
) to the
post-induction value (Clmax
The model will assume that
clearance is correlated to enzyme level, which increases
exponentially with time.
Clearance at any time, t, (Clt
will thus be described as:
The parameters tlag
represent the time
before start of induction and the first-order rate constant
describing the rate of induction, respectively.
Alternatively, clearance will be described using a time dependent
represents the maximum fractional increase in
enzyme levels, T50
the time after the lag-time that
induction is half-complete, and tlag
is the lag time for
the initiation of induction.
To account for CYP2B6 genotype
differences in induction using either model, Clmax
will be allowed to differ by genotype.
The model will be flexible
enough for the best predictions to be made.
Inter-individual variability (IIV) in pharmacokinetic parameters will
be modeled using log-normally distributed errors (Eq 4):
is the population typical parameter estimate,
is a random normal deviate with mean = 0 and variance =
IIV parameters will not be retained in the model if they lead to
numerical difficulties in minimization or the covariance step, or
when they have inadequate precision as seen by large standard errors
Covariate analysis will be performed using a forward-selection
(α=0.05) followed by backward elimination (α=0.01)
method. Each covariate-parameter relationship
will first be tested in a univariate manner. Covariates with one
degree of freedom will be included in the forward selection if they
reduce the OFV by at least 3.84, corresponding to a p-value of <0.05.
The full covariate model will be reached when the addition of further
covariate-parameter relationships does not decrease the OFV to the
specified criteria. The covariate-parameter relationships will be
re-examined in the backward deletion step in a manner similar to the
forward inclusion step but reversed with stricter criteria,
corresponding to a significance level of α = 0.01.
The bootstrap method will be used. This will involve a re-sampling
technique where a sufficiently large number of new datasets will be
generated by randomly sampling with replacement individuals out of
the original dataset. Parameter estimates will then obtained for each
bootstrap dataset and summary statistics will be applied to the
distribution of the estimates. 1000 bootstrap datasets will be
generated and each evaluated using the respective PK –PD PD
model. The results from those estimation run where NONMEM was able to
calculate the variance-covariance matrix (i.e., a successful
covariance step), the 5th and 95th percentiles of the parameter
distribution were derived representing the lower and the upper bound
of a nonparametric 90% confidence interval. The bootstrap analysis
will be performed with PsN (Perl speaks NONMEM, versions 2.2.3 to
Pharmacokinetic simulations will be
using the final population model to evaluate the influence of
rifampicin co-treatment and CYP2B6*6 status on concentrations
in the steady-state dosing interval in patients
after 21 weeks of treatment, a time that allows enzyme
induction to be maximal.
Simulations will be
performed for rifampicin co-treatment and each CYP2B6*6
status, with simulated patients receiving a 600 mg oral daily dose as
Log-normally distributed patient weights will be
simulated with a variance of the log-weight distribution similar to
that of the observed patient dataset. Proportions
of subjects with trough concentrations falling below the minimum
effective concentration (<1 µg/mL or 3.2 µM) or at
greater risk for toxicity (>4 µg/mL or 12.7 µM) will
be determined for each sub population before predictions of
drug concentrations and associated virologic
decay and immunologic
recovery rates using viral loads and CD4 counts are compared to
provide efavirenz dosing recommendations for
Ugandan HIV patients with or without TB co-treatment, as well as the
different CYP2B6 genotype clusters.
The outcomes of this study will include efavirenz dose
recommendations for Ugandan HIV-1 infected patients with or without
rifampicin co-treatment and individuals carrying different genotypes
of CYP2B6 516GT (GG, GT & TT).
The study findings will guide
population and sub-population based efavirenz dozing with the
ultimate aim of optimizing its use in HIV management particularly
among the African population.
The model that best fits the data will
be documented and published for future efavirenz population dose
The authors thank all patients for their
participation in the study, the CTN, CIHR Canadian HIV Trials Network
for offering to sponsor the current project through an international
the Swedish International Development
Cooperation Agency, SIDA, for the grants (grant number. SWE 2004–098,
HIV-2006-031, SWE 2007–270, Makerere University - Karolinska
Institutet research collaboration) that were used for collection of
data used for this project.
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Cite this paper
Mukonzo, J. K. (2013). Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population. Open Science Repository Pharmaceutics, Online(open-access), e70081939. doi:10.7392/Pharmaceutics.70081939
Mukonzo, Jackson K. “Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population.” Open Science Repository Pharmaceutics Online.open-access (2013): e70081939. Web. 10 Mar. 2013.
Mukonzo, Jackson K. “Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population.” Open Science Repository Pharmaceutics Online, no. open-access (March 11, 2013): e70081939. http://www.open-science-repository.com/optimization-of-efavirenz-dosing-during-treatment-of-hiv-1-infected-adults-in-an-african-population.html.
Mukonzo, J.K., 2013. Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population. Open Science Repository Pharmaceutics, Online(open-access), p.e70081939. Available at: http://www.open-science-repository.com/optimization-of-efavirenz-dosing-during-treatment-of-hiv-1-infected-adults-in-an-african-population.html.
1. J. K. Mukonzo, Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population, Open Science Repository Pharmaceutics Online, e70081939 (2013).
1. Mukonzo, J. K. Optimization of Efavirenz Dosing During Treatment of HIV-1 Infected Adults in an African Population. Open Science Repository Pharmaceutics Online, e70081939 (2013).
Research registered in the DOI resolution system as: 10.7392/Pharmaceutics.70081939.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.