Skip Navigation LinksHome > December 22, 2000 - Volume 14 - Issue 18 > Plasma population pharmacokinetics and penetration into cere...
AIDS:
Clinical Science

Plasma population pharmacokinetics and penetration into cerebrospinal fluid of indinavir in combination with zidovudine and lamivudine in HIV-1-infected patients

Zhou, Xiao-Jiana; Havlir, Diane V.b; Richman, Douglas D.b; Acosta, Edward P.a; Hirsch, Martinc; Collier, Ann C.d; Tebas, Pabloe; Sommadossi, Jean-Pierrea; the AIDS Clinical Trials Group Study 343 Investigators

Free Access
Article Outline
Collapse Box

Author Information

From the aDepartments of Clinical Pharmacology and Medicine, Birmingham Veteran Affairs Medical Center, Center for AIDS Research, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, the bUniversity of California at San Diego and San Diego Veterans Affairs Medical Center, San Diego, California, the cInfectious Disease Unit and AIDS Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, the dUniversity of Washington School of Medicine, Seattle, Washington and eWashington University, St Louis, Missouri, USA.

Requests for reprints to Dr J.-P. Sommadossi, Department of Clinical Pharmacology, University of Alabama at Birmingham, 1670 University Boulevard, VH G019, Birmingham, Alabama, USA.

Received: 8 June 2000;

revised: 22 August 2000; accepted: 4 September 2000.

Sponsorship: This work was supported by the AIDS Clinical Trials Group of NIAID. Indinavir was provided by Merck; zidovudine and lamivudine were provided by Glaxo Wellcome.

Collapse Box

Abstract

Objectives: To evaluate plasma population pharmacokinetics and penetration into cerebrospinal fluid (CSF) by indinavir (IDV) in HIV-infected individuals receiving IDV, zidovudine and lamivudine.

Methods: Plasma population pharmacokinetic analysis was performed on 805 IDV plasma values from 171 patients, using a non-linear mixed-effects modeling approach. CSF data from 19 patients were analyzed using an individual approach.

Results: Mean individual Bayesian estimates for oral clearance (CL) and volume of distribution (V) by the final model that incorporated interoccasion variability were 0.75 l/h per kg [coefficient of variation (CV) 54.8%] and 1.74 l/kg (CV 82.7%), respectively. Mean model-predicted plasma IDV level at 8 h, maximal level, area under the plasma level–time curve up to 8 h and plasma half-life were 0.42 μmol/l (CV 57.5%), 9.51 μmol/l (CV 47.3%), 29.56 μmol/l⋅h (CV 46.9%) and 1.50 h (CV 20.9%), respectively. The mean IDV CSF level was 0.11 μmol/l (CV 49.7%) and the mean CSF:plasma concentration ratio was 0.017.

Conclusions: Population estimates of pharmacokinetic parameters of IDV and its CSF penetration were in excellent agreement with previously reported data from individual analyses. Intraindividual interoccasion variability of IDV pharmacokinetics was estimated to be of similar order of magnitude to its interindividual variability, which may affect response to long-term antiretroviral therapy involving IDV. CSF levels of IDV exceeded its in vitro 95% inhibitory concentration of HIV replication. Given that CSF is virtually free of protein, viral suppression in the central nervous system should be achievable with an IDV-containing regimen.

Back to Top | Article Outline

Introduction

Combination antiretroviral therapy involving HIV protease inhibitors and nucleoside reverse transcriptase inhibitors can rapidly suppress plasma viral load to undetectable levels and maintain such beyond-threshold levels for prolonged periods of time [1–3]. Potent multiple drug regimens are, however, complex and associated with uncertain long-term toxicities and cost issues. Therefore, the search for a simple but effective maintenance therapy is warranted.

The AIDS Clinical Trials Group (ACTG) study 343 was designed to assess whether a less-intensive regimen would be sufficient for maintenance therapy after an initial intensive induction therapy with a potent multidrug regimen [4]. A combination of indinavir (IDV) plus zidovudine and lamivudine was selected as the initial induction therapy based on the virologic response and tolerability [1–3]. Following the induction therapy, patients with plasma HIV RNA < 200 copies/ml were randomly assigned to either continue with the triple regimen or to receive two less potent regimens: IDV monotherapy or a combination of zidovudine and lamivudine. The triple drug regimen proved better than IDV alone or zidovudine plus lamivudine in maintaining suppression of plasma HIV RNA [4].

A pharmacology substudy was implemented during ACTG 343 to evaluate the plasma population pharmacokinetics and cerebrospinal fluid (CSF) penetration of IDV. Population pharmacokinetics of IDV were analyzed using sparse plasma samples collected throughout the study period. Population and Bayesian individual pharmacokinetic parameters were estimated together with interindividual variability and interoccasion variability. The influence of potential covariates, including body weight, age, gender, race and co-medication, on IDV plasma kinetics was examined. CSF penetration of the drug was evaluated by calculating the CSF:plasma ratio of IDV levels.

Back to Top | Article Outline

Patients and methods

Study design and patients

ACTG 343 was a phase II, multicenter, randomized double-blind clinical trial comparing the antiretroviral activity of three maintenance regimens in patients whose plasma HIV-1 RNA levels were first suppressed by a 24-week induction therapy with a potent three drug combination [4]. The study protocol was approved by institutional review boards of all participating centers and written informed consents were obtained from all subjects. Major inclusion criteria were HIV-infected adults with a CD4 cell count of at least 200 × 106 cells/l and a plasma level of HIV RNA of at least 1000 copies/ml at study entry. Subjects receiving more than 2 weeks of HIV therapy based on a protease inhibitor or any previous lamivudine or abacavir were not eligible. Other inclusion and exclusion criteria were previously documented [4]. During the induction phase of the study, all patients received an open-label triple drug combination with 800 mg IDV every 8 h, 150 mg lamivudine every 12 h and 300 mg zidovudine every 12 h for 6 months. Patients with plasma HIV RNA < 200 copies/ml at week 16, 20 and 24 of the induction phase were then randomized to receive one of the three maintenance regimens in a double-blind manner: IDV monotherapy, lamivudine plus zidovudine, or the original triple therapy. Drugs were administered at their original daily doses during the maintenance therapy. A total of 509 subjects were enrolled in ACTG 343. For the plasma population pharmacokinetic study, the initial target accrual was 200 subjects; 171 actually participated in this study; 19 were included in the evaluation of CSF penetration of IDV. All subjects who were followed at sites where facilities were available to obtain and process specimens for pharmacokinetic studies were provided with the opportunity to participate in the study.

Back to Top | Article Outline
Sampling schedule and analytical methods

Plasma population pharmacokinetics of IDV were analyzed using sparse samples collected at different occasions throughout the study: for trough levels (6–10 h) at weeks 4, 12, 20 and 24 during induction phase and at weeks 2, 4, 16 and 40 during maintenance therapy and by the end of therapy; for peak levels (0.5-1 h) at the time of randomization to maintenance therapy and by the end of therapy. Subjects were instructed to take all assigned study medications simultaneously. Blood samples (10 ml) were drawn into heparinized tubes and centrifuged at 2000 ×g for 10 min to obtain plasma. A total of 805 IDV plasma levels from 171 patients (mean 4.7 per individual) collected from 640 visits (mean 1.3 per visit) were obtained. Of the 805 samples, 474 (58.9%) were collected up to 8 h after dosing and 331 (41.1%) were obtained between 8 and 14 h after dosing. Of all plasma IDV levels available for non-linear mixed-effects model (NONMEM) analysis, 579 (71.9%) were from the triple regimen and 226 (28.1%) from IDV monotherapy during maintenance phase. Among the 171 patients, 17 had one visit, 81 had two to four visits and 73 had five visits. Among patients who had at least two visits (154), 103 had multiple samples taken on at least one occasion and from these, 43 had multiple samples on at least two occasions. For the 68 individuals who had one sample per visit, 51 had at least two visits in total and 35 had three to five visits.

CSF samples were collected through lumbar puncture 1–4 h after drug administration at week 24. A total of 19 samples were obtained. Plasma and CSF samples were stored at −20°C until analysis. Plasma and CSF levels of IDV were measured using a high-performance liquid chromatographic method previously reported [5]. This method had a lower limit of quantification of 25 ng/ml, and intra- and interassay variability of less than 15%.

Back to Top | Article Outline
Pharmacokinetic analysis

Plasma population pharmacokinetic analysis of IDV was performed using the NONMEM computer program (double precision, version V) [6]. A first-order conditional estimation method that gives individual Bayesian estimates was employed. A one-compartment model with first-order absorption and first-order elimination as implemented in NONMEM routine ADVAN2 was used. Basic pharmacokinetic parameters were absorption rate constant (KA), oral clearance (CL) and volume of distribution (V). IDV was only administered by the oral route and, therefore, the parameters termed ‘‘clearance’’ and ‘‘volume of distribution’’ represent the ratios of these parameters to the unknown absolute bioavailability of the drug.

The variances of log KA, log CL and log V, associated with interindividual variability were assumed to be constant. Covariance was also estimated. The availability of plasma samples from different visits or occasions allowed the estimation of interoccasion variability of IDV pharmacokinetic parameters for an individual [7]. The variances of log KA, log CL and log V associated with interindividual variability were assumed to be constant and again covariance was estimated.

Since larger intraindividual variability was likely to be seen with samples drawn closer to the time of dosing, reflecting variability of the rate of absorption, a mixture proportional error model was used to describe residual variability:Cij =Ĉij(1 + θipij), where Cij and Ĉij are, respectively, the i th measured and the model-predicted plasma concentrations of individual j; ∊ij is the residual intraindividual random error with zero mean and variance σ2, and θip is an increment proportion (ip) for which a value is to be estimated, but is fixed to 1 for tj > 2 h.

The correlation between some continuous or categorical covariates (body weight, age, gender, race and co-medication) and the structural pharmacokinetic parameters including CL, V and KA were assessed as follows. Briefly, the basic model lacking any covariates and interoccasion variability was determined and the corresponding minimum value of objective function (MVOF) as supplied by NONMEM was set as the reference value. Potential covariates were then separately incorporated into the structure model of pharmacokinetic parameters and corresponding NONMEM runs were performed. The change in MVOF as the result of incorporation of a potential covariate from the reference value (ΔMVOF) approximates a χ2 distribution and was regarded as statistically significant (P < 0.05) if it was > 3.84. The full model incorporating significant covariates was then built and further refined by deleting covariates that, when set to their null value, failed to increase MVOF significantly (P > 0.05). Subsequently, the final model incorporating significant covariates as well as interoccasion variability was built and individual Bayesian estimates of the structural pharmacokinetic parameters by the final model were obtained. Other pharmacokinetic parameters derived from the final model include area under the plasma level–time curve up to 8 h after dose (AUC8h) by the trapezoidal rule and plasma half-life as 0.693/ K where K is the elimination rate constant CL/ V. The time (tmax) to maximal plasma concentration (Cmax) and Cmax were calculated according to classical steady-state formulae for repeated oral doses [8], while trough levels (C8h), equivalent to C0h, were part of the NONMEM output.

Penetration of IDV into the central nervous system was evaluated by calculating the CSF:plasma ratio of IDV levels. Because of practical issues associated with lumbar puncture, it was impossible to obtain CSF and plasma samples at the same time. Therefore, plasma levels were calculated using the final model for the time of CSF sampling.

Back to Top | Article Outline

Results

Plasma population pharmacokinetics of indinavir

Table 1 summarizes patient characteristics at baseline and Fig. 1 shows a scatter plot of pooled plasma IDV levels versus time.

Fig. 1
Fig. 1
Image Tools
Table 1
Table 1
Image Tools

A one-compartment model with first-order absorption and first-order elimination with CL, V and KA as basic structural parameters, as implemented in the ADVAN2 and TRANS2 routines of NONMEM, was used to describe IDV plasma population kinetics. A basic model with the above structural parameters as well as statistical parameters describing interindividual variability was built. Results from the basic model lacking interoccasion variability are presented in Table 2.

Table 2
Table 2
Image Tools

A number of potential covariates were assessed for their effects on pharmacokinetic parameters of IDV. These covariates included body weight and age (linear), and gender, race and co-medication (categorical). Initial covariate analysis (see Methods) identified age and race as significant covariates for CL, V and KA. ΔMVOF was −31.7, −38.7 and −14.1 for age, and −23.2, −21.7 and −22.2 for race with the CL, V and KA parameters, respectively. In contrast, body weight, gender and concomitant zidovudine and lamivudine did not appear to affect IDV pharmacokinetic parameters. A full model incorporating the identified covariates was built and further refined by setting them, one by one, to their null value (zero). This step eliminated the apparent effects of age on CL and KA, as well as race on CL, V and KA (P > 0.05). A model retaining age in the V model was obtained.

The availability of multiple plasma samples collected from different visits allowed an estimate of individual variability within the same subject across different occasions for structural pharmacokinetic parameters. Variances and co-variances associated with interoccasion variability were incorporated into the refined model with age as a covariate for V. This led to a highly significant fall in MVOF of 317 from the basic model. Further refinement of the model by deleting age from the V model resulted in a statistically significant (P < 0.02) increase in the objective function value. Therefore, the initial basic model with age in the V model along with interoccasion variability was considered as the final model: CL = 54.4 l/h ;V = 117 + 0.581(age − 37) (l);KA = 2.481/h. Model estimates for the final model are detailed in Table 2. The residual variability from the final model [coefficient of variation (CV) 27.2%] was much smaller than that from the basic model (66%). A simulated plasma pharmacokinetic profile of IDV by using the population typical parameter estimates is shown in Fig. 1. A plot of weighted residuals versus final model-predicted IDV plasma levels is displayed in Fig. 2. Mean individual Bayesian estimates of CL and V, normalized by body weight, were 0.75 l/h per kg (CV 54.8%) and 1.74 l/kg (CV 82.7%), respectively. Mean values of other derived pharmacokinetic parameters were 1.50 h (CV 20.9%) for half-life, 0.87 h (CV 13.2%) for tmax, 9.51 μmol/l (CV 47.3%) for Cmax, 0.42 μmol/l (CV 57.5%) for C8h, and 29.56 μmol/l⋅h (CV 46.9%) for AUC8h As can be seen from Fig. 1, a large portion of plasma samples (331 of a total of 805; 41.1%) was obtained beyond 8 h after administration. Median sampling time for these levels was 9.5 h (range 8.1–13.5). Bayesian estimation of the median IDV concentration at this time was 0.20 μmol/l (CV 77.7%), which is in excellent agreement with the experimental median value within the same time interval: 0.19 μmol/l (CV 79.9%).

Fig. 2
Fig. 2
Image Tools

Trough levels (C8h) and AUC are generally considered as indicators of drug exposure. For patients with at least two visits, interoccasion variability of C8h and AUC8h was calculated for each individual expressed as the CV of the parameters over different occasions. As depicted in Fig. 3, while this did range from < 10% to > 60%, most subjects had interoccasion variability of 20–40% for the parameters.

Fig. 3
Fig. 3
Image Tools
Back to Top | Article Outline
Penetration of indinavir into cerebrospinal fluid

The penetration of IDV into the central nervous system was evaluated by measuring IDV levels in CSF and in plasma in a smaller group of 19 patients. Measured levels of IDV in CSF and corresponding model-predicted plasma levels of IDV are shown in Fig. 4. IDV levels in CSF in these patients were variable, ranging from 0.032 to 0.25 μmol/l, with a mean of 0.11 μmol/l (CV 49.7%). Average CSF sampling time was 1.4 h (range 0.5–3.3). Corresponding mean plasma IDV level was 10.28 μmol/l (CV 51.0%). The CSF:plasma ratio of IDV levels, an indicator of CSF penetration of the drug, ranged from 0.002 to 0.051 with a mean of 0.017 (CV 88.6%).

Fig. 4
Fig. 4
Image Tools
Back to Top | Article Outline

Discussion

NONMEM analysis using sparsely collected samples has been previously applied to evaluate plasma population pharmacokinetics for several nucleoside and non-nucleoside HIV reverse transcriptase inhibitors, including zidovudine, didanosine and nevirapine, and the protease inhibitor saquinavir during combination therapy [9,10]. Implemented in large-scale studies, these population studies have provided a unique opportunity to define pharmacokinetic inter- and intraindividual variability and interoccasion variability associated with long-term antiretroviral therapy and to identify covariates that significantly affect pharmacokinetic behavior of these drugs. Results from these studies can serve to optimize anti-HIV therapy.

Pharmacokinetics of IDV was previously studied in healthy volunteers and HIV-infected patients during small-scale phase I and/or II clinical trials following single or multiple oral doses [11]. Plasma pharmacokinetic parameters of IDV obtained from the present population study of the drug dosed at 800 mg every 8 h in 171 patients are 0.87 h, 9.51 μmol/l, 0.42 μmol/l and 29.56 μmol/l.h for tmax, Cmax, C8h and AUC8h, respectively. These results are in very good agreement with previous data as summarized in the manufacturer's package insert at the recommended dose and frequency of the drug (800 mg every 8 h):tmax, Cmax, C8h and AUC8h being 0.8 h, 12.62 μmol/l, 0.25 μmol/l and 30.69 μmol/l.h, respectively [12].

Clinical pharmacokinetics of IDV are associated with substantial interindividual variability, which is at least partly responsible for the variability in viral response to an IDV-containing regimen [13–15]. In addition to interindividual variability, pharmacokinetic behavior of drugs can also vary in time as a result of metabolic changes, for example in pathophysiological conditions such as renal and hepatic function. Because of the chronic nature of antiretroviral therapy, it is, therefore, of particular importance to define pharmacokinetic variability of anti-HIV drugs across different occasions within an individual (interoccasion variability). In the present study, as illustrated in Fig. 1, plasma levels of IDV varied extensively at any given time. This high variability could account for much of the variability seen among patients taking IDV with regard to both activity and toxicity. Variability (interoccasion and interindividual) of the structural parameters was successfully estimated with good precision (Table 2). Interoccasion variability (as CV) of CL and V (not normalized to body weight) were 56.7% and 60.7%, respectively, which was of comparable magnitude to their respective interindividual variability, 52.7% and 70.2%. Incorporation of interoccasion variability in the model successfully explained a portion of the residual variability, reducing this to 27.2% in the final model compared with 66.0% in the basic model.

Trough levels are defined as concentrations immediately preceding the next dose. These levels have been shown to correlate with HIV RNA response to an IDV-containing regimen [13–15]. For IDV taken every 8 h, plasma concentrations at 8 h postdosing are generally regarded as trough levels. In the present study (Fig. 1), a large number of plasma samples were obtained beyond 8 h, the indicated time to take the next dose, up to more than 13 h following the previous dose. Among the 331 samples collected after 8 h, more than two thirds were obtained later than 9 h, of which half were drawn 10 h after IDV administration. It should be pointed out that most of these late samples were drawn in the morning before the subjects being given the dose for pharmacokinetic sampling. IDV levels associated with these samples represent, therefore, the morning troughs of last night's dose. Given the short plasma half-life of the drug (1.5 h), trough levels beyond 10 h are much lower than those at 8 h. Median individual Bayesian estimates of IDV levels at 10 and 12 h post dosing were 0.13 (CV 79.1%) and 0.05 μmol/l (CV 86.1%), respectively. Despite the fact that a patient may be compliant by taking all three doses each day, it is conceivable that the time elapsing between the evening dose and the next morning dose could be much longer than 8 h, resulting in suboptimal drug exposure, which may compromise virological response over time.

Pharmacokinetics of IDV can be affected by other factors. Published data have focused primarily on drug–drug interactions between IDV, which is metabolized by hepatic CYP3A, and some co-administered drugs that influence IDV metabolism through induction or inhibition of this subfamily of enzymes [11,16]. In the present study, we examined a number of covariates that commonly affect pharmacokinetics of drugs. These factors included patient demographics and treatment regimen. The effects of these covariates were evaluated in the basic model without interoccasion variability to avoid excessive computation. IDV was administered in combination with lamivudine and zidovudine during the induction phase in all subjects and in one arm during maintenance therapy. No metabolic drug–drug interactions between IDV and these nucleoside analogs were anticipated, since they undergo different biotransformation processes. During the process of identifying covariates, incorporation of the factor ‘regimen’ (IDV alone versus in combination) into the model did not result in a better fit, demonstrating the absence of an effect of concomitant nucleoside drugs on IDV.

Body weight, a covariate that commonly correlates with CL and V, did not significantly influence IDV pharmacokinetics. Nevertheless, CL and V were still normalized to body weight for the purpose of uniformity and comparison with previously reported data. IDV is mainly cleared through hepatic CYP3A-mediated metabolism [16]. In a previous animal study, gender was identified to affect IDV CL, with male rats exhibiting a metabolic clearance twice as high as that of females [17]. This gender-dependent pharmacokinetics was caused by differences in the activity of CYP3A. Such a gender-dependent IDV CL, however, was not found in vivo in primates (monkey) or in vitro using human hepatic microsomes [17,18]. In the present study, gender did not affect CL when it was incorporated into the CL model, with male and female patients exhibiting comparable CL values (0.71 and 0.88 l/h per kg in males and females, respectively).

Among the patient demographics examined, age was the only covariate that significantly influenced IDV pharmacokinetics, with older subjects exhibiting a larger value for V IDV.CL remained unrelated to age in the studied age range. Since the elimination rate constant is related to CL and V, an increase in V with a stable CL results in an decrease in this value and an increase in the half-life of IDV as people age. It has been demonstrated that the aging process results in a decline in hepatic CYP3A-mediated oxidative metabolism of xenobiotics [18]. However, metabolism of some endogenous substrates indicative of CYP3A activity, such as testosterone 6β-hydroxylation, is basically constant with increasing age [19,20]. In addition, an in vitro study that evaluated the effect of aging on human CYP3A activity also failed to show a correlation between age and CYP3A activity [18]. These apparent paradoxes warrant further investigation of IDV pharmacokinetics in elderly subjects. The age-associated increase in the value of V for IDV may be related to its high lipophilicity. Lipophilic drugs such as diazepam were shown to exhibit an increased V in elderly individuals as a consequence of an aging-related increase in adipose tissue and a decrease in lean body mass relative to total body weight [21]. The age-related change in IDV pharmacokinetics, as identified by the present study, should, however, have little clinical consequences since parameters underlying IDV exposure (AUC8h and trough levels) were not significantly influenced by age.

The central nervous system is an important HIV sanctuary [22]. The effectiveness of antiretroviral therapy depends on the ability of antiretroviral agents to reach this area. IDV is the only protease inhibitor that achieves CSF levels that exceed its in vitro 95% inhibitory concentration for HIV replication (0.025–0.1 μmol/l) [23,24]. Its use, therefore, presents an opportunity to suppress viral replication in the central nervous system. HIV RNA in the CSF could not be detected in a study of combination therapy involving IDV [25]. A recent study showed that an IDV-containing regimen led to > 1 log10 copies/ml decline in CSF HIV RNA compared with reference treatments that contained no protease inhibitors [26]. CSF penetration of the drug has been previously documented [26–29]. For practical reasons, a single CSF sample was obtained per subject per visit in most cases. CSF IDV levels ranged from 0.05 to 0.66 μmol/l, with sampling occurring at 1–5 h after dosing [26–29]. In the present study, the mean CSF IDV level in 19 patients was 0.11 μmol/l, with an average sampling time of 1.4 h postadministration; this is consistent with other reported data. The failure observed in the IDV monotherapy arm [4] is, therefore, unlikely to be a result of insufficient CNS exposure of the drug. Mean CSF:plasma IDV ratio was 0.017. This ratio has so far been used as a measure of the extent of IDV CSF penetration. However, recently published data on IDV CFS penetration using levels measured up to 16 h after dosing demonstrated that IDV CSF levels remained constant over time with the standard regimen [26]. Plasma drug levels declined rapidly, resulting in an apparent time-dependent change in the CSF:plasma ratio. The ratio was approximately 1 at 8 h postdose and 2 at 16 h [26]. Although the CSF:plasma ratio of Cmax is generally accepted as a measure of CSF penetration, a more accurate approach would be to calculate the CSF:plasma ratio of IDV AUC through population analysis using sparse CSF samples.

In conclusion, plasma population pharmacokinetics of IDV in combination with zidovudine and lamivudine was studied in 171 HIV-infected patients. IDV pharmacokinetic parameters and associated intersubject variability were consistent with previously reported data. IDV pharmacokinetics were shown to exhibit interoccasion variability at a magnitude that is comparable to its interindividual variability. IDV CSF levels measured from 19 patients were above the 95% inhibitory concentration of HIV replication. Given that CSF is virtually free of protein, viral suppression in the central nervous system should be achievable with an IDV-containing regimen.

Back to Top | Article Outline

Acknowledgments

The authors would like to thank the patients and staff who contributed to the study, Michele Turner at the University of Alabama at Birmingham for indinavir analysis, the participating ACTU pharmacology laboratory staff and the ACTG Operations Staff.

Back to Top | Article Outline

References

1. Hammer SM, Squires KE, Hughes MD. et al. A controlled trial of two nucleoside analogues plus indinavir in persons with human immunodeficiency virus infection and CD4 cell counts of 200 per cubic millimeter or less. :AIDS Clinical Trials Group 320 Study Team. N Engl J Med 1997, 337: 725 –733.

2. Gulick RM, Mellors JW, Havlir D. et al. Treatment with indinavir, zidovudine, and lamivudine in adults with human immunodeficiency virus infection and prior antiretroviral therapy. N Engl J Med 1997, 337: 734 –739.

3. Hirsch M, Steigbigel R, Staszewski S. et al. A randomized, controlled trial of indinavir, zidovudine, and lamivudine in adults with advanced human immunodeficiency virus type 1 infection and prior antiretroviral therapy. J Infect Dis 1999, 180: 659 –665.

4. Havlir DV, Marschner IC, Hirsch MS. et al. Maintenance antiretroviral therapies in HIV infected patients with undetectable plasma HIV RNA after triple-drug therapy. :AIDS Clinical Trials Group 343 Study Team. N Engl J Med 1998, 339: 1261 –1268.

5. Foisy ML, Sommadossi JP. Rapid quantification of indinavir in human plasma by high-performance liquid chromatography with ultraviolet detection. J Chromatogr B 1999, 721: 239 –247.

6. Beal SL, Sheiner LB. NONMEM User's Guide. San Francisco: University of California at San Francisco.

7. Karlsson MO, Sheiner LB. The importance of modeling interoccasion variability in population pharmacokinetic analyses. J Pharmacokinet Biopharmaceut 1993, 21: 735 –750.

8. Ritschel WA. Pharmacokinetics of multiple dosing. In:Handbook of Basic Pharmacokinetics. Edited by Ritschel WA. Hamilton: Drug Intelligence Publications; 1976: 218 –234.

9. Zhou XJ, Sheiner LB, D'Aquila RT. et al. Population pharmacokinetics of nevirapine, zidovudine, and didanosine in human immunodeficiency virus-infected patients. Antimicrob Agents Chemother 1999, 43: 121 –128.

10. Vanhove GF, Kastrissios H, Gries JM. et al. Pharmacokinetics of saquinavir, zidovudine, and zalcitabine in combination therapy. Antimicrob Agents Chemother 1997, 41: 2428 –2432.

11. Plosker GL, Noble S. Indinavir – a review of its use in the management of HIV infection. Drugs 1999, 58: 1165 –1203.

12. Merck Sharp & Dohme. Package insert for Crixivan.

13. Stein DS, Fish DG, Bilello JA, Preston SL, Martineau GL, Drusano GL. A 24-week open-label phase I/II evaluation of the HIV protease inhibitor MK-639 (indinavir). AIDS 1996, 10: 485 –492.

14. Acosta E, Henry K, Baken L, Page LM, Fletcher CV. Indinavir concentrations and antiviral effect. Pharmacotherapy 1999, 19: 708 –712.

15. Murphy RL, Sommadossi JP, Lamson M, Hall DB, Myers M, Dusek A. Antiviral effect and pharmacokinetic interaction between nevirapine and indinavir in persons infected with human immunodeficiency virus type 1. J Infect Dis 1999, 179: 1116 –1123.

16. Chiba M, Hensleigh M, Nishime JA, Balani SK, Lin JH. Role of cytochrome P450 3A4 in human metabolism of MK-639, a potent human immunodeficiency virus protease inhibitor. Drug Metab Dispos 1996, 24: 307 –314.

17. Lin JH, Chiba M, Chen IW, Nishime JA, Vastag KJ. Sex-dependent pharmacokinetics of indinavir: in vivo and in vitro evidence. Drug Metab Dispos 1996, 24: 1298 –1306.

18. Hunt CM, Westerkam WR, Stave GM. Effect of age and gender on the activity of human hepatic CYP3A. Biochem Pharmacol 1992, 44: 275 –283.

19. Crowley JJ, Cusack B., Jue SG, Coup JR, Park BK, Vestal RE. Aging and drug interactions. :II. Effect of phenytoin and smoking on the oxidation of theophylline and cortisol in healthy men. J Pharmacol Exp Ther 1988, 1245: 513 –523.

20. Wrighton SA, Brian WR, Sari MA. et al. Studies on the expression and metabolic capabilities of human liver cytochrome P-450IIIA5 (HLp3). Mol Pharmacol 1990, 38: 207 –213.

21. Greenblatt DJ, Abernethy DR, Shader RI. Pharmacokinetic aspects of drug therapy in the elderly. Ther Drug Monit 1986, 8: 249 –255.

22. Portegies P. HIV-1, the brain and combination therapy. Lancet 1995, 346: 1244 –1245.

23. Emini EA, Schleif WA, Deutsch P, Condra JH. In vivo selection of HIV-1 variants with reduced susceptibility to the protease inhibitor L-735,524 and related compounds. Adv Exp Med Biol 1996, 394: 327 –331.

24. Vacca JP, Dorsey BD, Schleif WA. et al. L-735,524: an orally bioavailable human immunodeficiency virus type 1 protease inhibitor. Proc Natl Acad Sci USA 1994, 91: 4096 –4100.

25. Gisslen M, Hagberg L, Svennerholm B, Norkrans G. HIV-1 RNA is not detectable in the cerebrospinal fluid during antiretroviral combination therapy. AIDS 1997, 11: 1194. 1194.

26. Martin C, Sonnerborg A, Svensson JO, Stahle L. Indinavir-based treatment of HIV-1 infected patients: efficacy in the central nervous system. AIDS 1999, 13: 1227 –1232.

27. Brinkman K, Kroon F, Hugen PW, Burger DM. Therapeutic concentrations of indinavir in cerebrospinal fluid of HIV-1-infected patients. AIDS 1998, 12: 537. 537.

28. Enting RH, Hoetelmans RM, Lange JM, Burger DM, Beijnen JH, Portegies P. Antiretroviral drugs and the central nervous system. AIDS 1998, 12: 1941 –1955.

29. Stahle L, Martin C, Svensson JO, Sonnerborg A. Indinavir in cerebrospinal fluid of HIV-1-infected patients. Lancet 1997, 350: 1823. 1823.

Keywords:

indinavir; population pharmacokinetics; cerebrospinal fluid penetration; combination antiretroviral therapy

© 2000 Lippincott Williams & Wilkins, Inc.

Login

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.