Hepatic and renal insufficiency due to co-infection, alcoholism, diabetes mellitus, family history, adverse effects of antiretrovirals and other factors are commonly seen in HIV-infected patients. Therefore, the use of antiretrovirals in this patient setting requires attention to the pharmacokinetic issues that clinicians must consider when prescribing highly active antiretroviral therapy for these patients. This review summarizes the current knowledge of the use of antiretrovirals in patients with hepatic or renal impairment, and makes dosing recommendations for this subpopulation of HIV-infected patients.

BACKGROUND AND OBJECTIVE:The purpose of the current study was to demonstrate proof-of-concept that monocarboxylate transporter (MCT) inhibition with L-lactate combined with osmotic diuresis increases renal clearance of γ-hydroxybutyrate (GHB) in human subjects. GHB is a substrate for human and rodent MCTs, which are responsible for GHB renal reabsorption, and this therapy increases GHB renal clearance in rats.METHODS:Ten healthy volunteers were administered GHB orally as sodium oxybate 50 mg/kg (4.5 gm maximum dose) on two different study days. On study day 1, GHB was administered alone. On study day 2, treatment of L-lactate 0.125 mmol/kg and mannitol 200 mg/kg followed by L-lactate 0.75 mmol/kg/hr was administered intravenously 30 minutes after GHB ingestion. Blood and urine were collected for 6 hours, analyzed for GHB, and pharmacokinetic and statistical analyses performed.RESULTS:L-lactate/mannitol administration significantly increased GHB renal clearance compared to GHB alone, 439 vs. 615 mL/hr (P=0.001), and increased the percentage of GHB dose excreted in the urine, 2.2 vs. 3.3% (P=0.021). Total clearance was unchanged.CONCLUSIONS:MCT inhibition with L-lactate combined with osmotic diuresis increases GHB renal elimination in humans. No effect on total clearance was observed in this study due to the negligible contribution of renal clearance to total clearance at this low GHB dose. Considering the nonlinear renal elimination of GHB, further research in overdose cases is warranted to assess the efficacy of this treatment strategy for increasing renal and total clearance at high GHB doses.

In a randomized trial, AIDS Clinical Trials Group (ACTG) protocol 5146 (A5146) investigated the use of therapeutic drug monitoring (TDM) to adjust doses of HIV-1 protease inhibitors (PIs) in patients with prior virologic failure on PI-based therapy who were starting a new PI-based regimen. The overall percentage of “PI trough repeats” such as rescheduled visits or redrawn PI trough specimens increased from 2% to 5% to 10% as the process progressed from the clinical sites, the pharmacology specialty laboratory, and the study team, respectively. Cumulatively, this represents a 17% rate of failure to obtain adequate PI trough sample. While targeting a turnaround of 7 days or less from sample receipt to a drug concentration report, 12% of the received specimens required a longer period to report concentrations. The implementation of dosing changes in the TDM arm were achieved within 7 days or less for 56% of the dose change events and within 14 days or less for 77% of dose change events. This quality assurance analysis provides a valuable summary of the specific points in the TDM process that could be improved during a multicenter clinical trial including: 1) shortening the timeline of sample shipment from clinical site to the laboratory; 2) performing the collection of PI trough specimen within the targeted sampling window by careful monitoring of the last dose times and collection times by the clinicians; 3) increasing patient adherence counseling to reduce the number of samples that are redrawn due to suspecting inconsistent adherence; and 4) decreasing the time to successful TDM-based dose adjustment. The application of some of these findings may also be relevant to single-center studies or clinical TDM programs within a hospital.

Objective: Whether therapeutic drug monitoring of protease inhibitors improves outcomes in HIV-infected patients is controversial. We evaluated this strategy in a randomized, open-label clinical trial, using a normalized inhibitory quotient (NIQ), which incorporates drug exposure and viral drug resistance. NIQs ≤ 1 may predict poor outcome and identify patients who could benefit from dose escalation. Design/methods: Eligible patients had a viral load ≥1000 copies/ml on a failing regimen, and began a new protease inhibitor containing regimen at entry. All FDA-approved protease inhibitors available during the study recruitment (June 2002–May 2006) were allowed. One hundred and eighty-three participants with NIQ ≤ 1, on the basis of their week 2 protease inhibitor trough concentration and pre-entry drug resistance test, were randomized at week 4 to standard of care (SOC) or protease inhibitor dose escalation (TDM). The primary endpoint was change in log10 plasma HIV-1 RNA concentration from randomization to 20 weeks later. Results: Ninety-one patients were randomized to SOC and 92 to TDM. NIQs increased more in the TDM arm compared to SOC (+69 versus +25%, P = 0.01). Despite this, TDM and SOC arms showed no difference in outcome (+0.09 versus +0.02 log10, P = 0.17). In retrospective subgroup analyses, patients with less HIV resistance to their protease inhibitors benefited from TDM (P = 0.002), as did black and Hispanic patients (P = 0.035 and 0.05, respectively). Differences between black and white patients persisted when accounting for protease inhibitor susceptibility. Conclusions: There was no overall benefit of TDM. In post hoc subgroup analyses, TDM appeared beneficial in black and Hispanic patients, and in patients whose virus retained some susceptibility to the protease inhibitors in their regimen.

BACKGROUND:The central nervous system may act as a sanctuary site for viral replication in the setting of low antiretroviral penetration. Data on lopinavir cerebrospinal fluid (CSF) trough concentration (C(trough)) values have yet to be reported. OBJECTIVE:To describe lopinavir CSF C(trough) values and compare them with a measure of HIV susceptibility. METHODS:In a prospective, open-label design, HIV-infected adults whose regimen included lopinavir/ritonavir 400/100-mg soft-gel capsules twice daily for at least 4 weeks were enrolled. Each subject had 8 plasma lopinavir concentrations determined over a 12-hour dosing interval and 1 CSF lopinavir C(trough) value determined at the end of the study. Linear regression methods tested for associations between CSF or CSF to plasma concentration ratio and covariates including pharmacokinetic parameters and CSF protein. RESULTS:Ten patients (7 male; median [range] +/- SD age 45.3 +/- 2.8 y) completed the study. Median (intraquartile range [IQR]) lopinavir plasma 0- to 12-hour area under the curve (AUC(0-12)) and minimum concentrations were 71.3 h x microg/mL (48.4-87.6) and 3.82 microg/mL (2.76-5.34). Median (IQR) CSF C(trough), paired plasma concentration, and time since last dose were 11,200 pg/mL (6760-16,400), 5.42 microg/mL (3.88-5.85), and 9.9 hours (9.7-10.2), respectively. Median (IQR) CSF to plasma concentration ratio was 0.225% (0.194-0.324). Lopinavir CSF C(trough) was above the median 50% inhibitory concentration (IC(50)) for wild-type HIV-1 (wtHIV-1) (1900 pg/mL) in all subjects. Lopinavir plasma AUC(0-12) (r(2) = 0.65; p = 0.009) and CSF protein (r(2) = 0.26; p = 0.006) were associated with lopinavir CSF concentration, while CSF protein (r(2) = 0.66; p = 0.008) was associated with CSF to plasma concentration ratio. CONCLUSIONS:Lopinavir CSF C(trough) was above the median IC(50) for wtHIV-1 replication in all patients receiving lopinavir/ritonavir 400/100-mg soft-gel capsules twice daily.

Objective To develop and validate a 48-hour gentamicin dosing regimen for infants born at <28 weeks' gestation. Study design Using previously published pharmacokinetic data, we performed Monte Carlo simulations for several candidate gentamicin dosing regimens. Oil the basis of these simulations, we changed dosing for infants horn at <28 weeks to 4.5 mg/kg every 48 hours. We then conducted an observational study of 30 infants on this new regimen and compared serum gentamicin levels with 60 histrorical control subjects who received 2.5 mg/kg every 25 hours. Results Infants in the 48-hour group achieved higher gentamicin peaks (mean 9.43 mu g/mL vs 6.0 mu g/mL vs P < .001) and lower gentamicin troughs (mean 1.08 mu g/mL vs 1.54 mu g/mL, P < .001) and the 48-hour group infants had a gentamicin peak <6 mu g/mL, versus 43% in the 24-hour group. With a goal for peaks of 6 to 12 mu g/mL, and for troughs of <1.5 mu g/mL, infants in the 48-hour group required fewer adjustments of their dosing regimens compared with the 24-hour group (26.7% vs 78.3%). Conclusions Gentamicin given every 48 hours to infants born at <28 weeks achieves optimal blood concentrations more frequently than does once-daily dosing. Monte Carlo simulations on the basis of pharmacokinetic modeling are useful to optimize drug closing in premature infants.

Hepatic and renal insufficiency due to co-infection, alcoholism, diabetes mellitus, family history, adverse effects of antiretrovirals and other factors are commonly seen in HIV-infected patients. Therefore, the use of antiretrovirals in this patient setting requires attention to the pharmacokinetic issues that clinicians must consider when prescribing highly active antiretroviral therapy for these patients. This review summarizes the current knowledge of the use of antiretrovirals in patients with hepatic or renal impairment, and makes dosing recommendations for this subpopulation of HIV-infected patients.

The AIDS Clinical Trials Group designed and implemented a prospective, randomized, strategy trial in antiretroviral-experienced, HIV-infected patients to evaluate the virologic impact of protease inhibitor dose escalation in response to therapeutic drug monitoring (TDM) with an inhibitory quotient, which integrates both drug exposure and viral drug resistance. In the process of developing this clinical trial, several unique challenges were identified that required innovative solutions. The major challenge was the need to integrate resistance testing, pharmacokinetic data, medication adherence, toxicity data, clinical assessments, randomization assignment, and protocol-specified clinical management in a way that could be utilized in real time by the protocol team, communicated promptly to the clinical sites, and transmitted accurately to the study database. In addition, the protocol team had to address the relative lack of commercially available TDM laboratories in the United States that were experienced in antiretroviral drug assays and a lack of familiarity with the principles of pharmacokinetic monitoring at participating clinical sites. This article outlines the rationale for the design of this strategy trial, specific barriers to implementation that were identified, and solutions that were developed with the hope that these experiences will facilitate the design and conduct of future trials of TDM.

The purpose of this study was to examine the pharmacokinetics of quercetin aglycone as well as its conjugated metabolites and to develop a population pharmacokinetic model for quercetin that incorporates enterohepatic recirculation. The stability of quercetin in different matrices at various temperatures and pH, and the quercetin content of six capsules of the herbal preparation Quercetin-500 Plus were determined by HPLC. Subjects received quercetin 500 mg three times daily and blood and urine samples were obtained. The concentration of quercetin aglycone and conjugated metabolites were assayed using a liquid chromatography-tandem mass spectrometry assay. Pharmacokinetic parameters were determined using noncompartmental analysis with WinNonlin. A population compartment model incorporating input from the gallbladder was developed to account for the enterohepatic recirculation observed with quercetin. The oral clearance (CL/F) was high (3.5 x 10(4)l/h) with an average terminal half-life of 3.5 h for quercetin. The plasma concentration versus time curves exhibited re-entry peaks. A one-compartment model that included enterohepatic recirculation best described the plasma data. This represents the first comprehensive evaluation of the pharmacokinetics and enterohepatic recirculation of quercetin in humans. Population pharmacokinetic models adapted for enterohepatic recirculation allowed an assessment of the magnitude and frequency of the enterohepatic recirculation process.

The Journal of Clinical PharmacologyVolume 47, Issue 12 p. 1580-1586 A Randomized Study of the Bioavailability of Different Formulations of Coenzyme Q10 (Ubiquinone) Dr Radu Constantinescu MD, Dr Radu Constantinescu MD Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr Michae P. McDermott PhD, Dr Michae P. McDermott PhD Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr Robert DiCenzo PharmD, Dr Robert DiCenzo PharmD Department of Pharmacy Practice, University at Buffalo, SUNY Buffalo, New YorkSearch for more papers by this authorElisabet A. de Blieck MPA, CCRC, Elisabet A. de Blieck MPA, CCRC Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr H. Christopher Hyson MD, FRCPC, Dr H. Christopher Hyson MD, FRCPC London Health Sciences Centre, London, Ontario, CanadaSearch for more papers by this authorDr M. Flint Beal MD, Dr M. Flint Beal MD Weill Medical College/Cornell University, New YorkSearch for more papers by this authorDr Edwar M. Bednarczyk PharmD, Dr Edwar M. Bednarczyk PharmD Department of Pharmacy Practice, University at Buffalo, SUNY Buffalo, New YorkSearch for more papers by this authorDr Mikhail Bogdanov MD, PhD, Dr Mikhail Bogdanov MD, PhD Weill Medical College/Cornell University, New YorkSearch for more papers by this authorMs Lind J. Metakis BA, Ms Lind J. Metakis BA Weill Medical College/Cornell University, New YorkSearch for more papers by this authorDr Susa E. Browne PhD, Dr Susa E. Browne PhD Weill Medical College/Cornell University, New YorkSearch for more papers by this authorMs Beverl J. Lorenzo BS, Ms Beverl J. Lorenzo BS Weill Medical College/Cornell University, New YorkSearch for more papers by this authorDr Bernard Ravina MD, MSCE, Dr Bernard Ravina MD, MSCE Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr Karl Kieburtz MD, MPH, Corresponding Author Dr Karl Kieburtz MD, MPH Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkAddress for correspondence: Karl Kieburtz, MD, MPH, 1351 Mt Hope Avenue, Suite 223, Rochester, NY 14620; e-mail: [email protected].Search for more papers by this author Dr Radu Constantinescu MD, Dr Radu Constantinescu MD Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr Michae P. McDermott PhD, Dr Michae P. McDermott PhD Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr Robert DiCenzo PharmD, Dr Robert DiCenzo PharmD Department of Pharmacy Practice, University at Buffalo, SUNY Buffalo, New YorkSearch for more papers by this authorElisabet A. de Blieck MPA, CCRC, Elisabet A. de Blieck MPA, CCRC Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr H. Christopher Hyson MD, FRCPC, Dr H. Christopher Hyson MD, FRCPC London Health Sciences Centre, London, Ontario, CanadaSearch for more papers by this authorDr M. Flint Beal MD, Dr M. Flint Beal MD Weill Medical College/Cornell University, New YorkSearch for more papers by this authorDr Edwar M. Bednarczyk PharmD, Dr Edwar M. Bednarczyk PharmD Department of Pharmacy Practice, University at Buffalo, SUNY Buffalo, New YorkSearch for more papers by this authorDr Mikhail Bogdanov MD, PhD, Dr Mikhail Bogdanov MD, PhD Weill Medical College/Cornell University, New YorkSearch for more papers by this authorMs Lind J. Metakis BA, Ms Lind J. Metakis BA Weill Medical College/Cornell University, New YorkSearch for more papers by this authorDr Susa E. Browne PhD, Dr Susa E. Browne PhD Weill Medical College/Cornell University, New YorkSearch for more papers by this authorMs Beverl J. Lorenzo BS, Ms Beverl J. Lorenzo BS Weill Medical College/Cornell University, New YorkSearch for more papers by this authorDr Bernard Ravina MD, MSCE, Dr Bernard Ravina MD, MSCE Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkSearch for more papers by this authorDr Karl Kieburtz MD, MPH, Corresponding Author Dr Karl Kieburtz MD, MPH Department of Neurology, Clinical Trials Coordination Center, University of Rochester Medical Center, Rochester, New YorkAddress for correspondence: Karl Kieburtz, MD, MPH, 1351 Mt Hope Avenue, Suite 223, Rochester, NY 14620; e-mail: [email protected].Search for more papers by this author First published: 07 March 2013 https://doi.org/10.1177/0091270007307571Citations: 15Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. 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A method for the simultaneous determination of cyclophosphamide (CP), doxorubicin (dox), and doxorubicinol (dol) was developed and validated to analyze 400μL of plasma from patients receiving chemotherapeutic treatment with CP and dox. Final calibration ranges for the analytes were 0.440–60.0μg/mL for cyclophosphamide, 7.20–984ng/mL for dox and 3.04–104ng/mL for dol. The samples were prepared using solid phase extraction and analyzed using a gradient separation over a Waters Symmetry® C18, 2.1 by 30mm (Milford, MA) column. Detection was achieved in positive mixed reaction monitoring mode on a triple quadrupole mass spectrometer.

A method for the determination of lopinavir (LPV) concentrations in cerebral spinal fluid (CSF) and plasma ultrafiltrate (UF) was developed and validated to analyze clinical specimens from patients receiving antiretroviral treatment with lopinavir/ritonavir. The CSF (400μL sample volume) final calibration range for LPV was 0.313–25.0ng/mL. The final calibration range for UF (50μL sample volume) was 1.25–100ng/mL. The samples were prepared using liquid–liquid extraction, concentrated, and analyzed using a reversed phase isocratic separation. Detection was achieved in positive mixed reaction monitoring mode on a triple quadrupole mass spectrometer. Isolation of LPV through chromatographic separation and proper selection of calibration matrix were important factors in achieving accurate results. Plasma UF was found to be an equivalent calibration matrix to CSF whereas plasma matrix produced a positive bias in samples with unknown concentrations. Artificial CSF media prepared chemically were biased and less superior than UF. Sources of plasma for the UF did not affect accuracy. Several CSF sources were tested for specificity of the method and LPV concentrations were accurately produced with atmospheric pressure chemical ionization source producing more accurate results than the electrospray source. The method successfully measured LPV concentrations in CSF that were previously undetectable by HPLC as well as UF from protein binding studies.

Study Objectives. To determine if quercetin, a bioflavonoid that inhibits p-glycoprotein, alters plasma saquinavir concentrations, and to explore the potential influence on intracellular concentrations.Design. Prospective pharmacokinetic analysis.Setting. University-affiliated general clinical research center.Subjects. Ten healthy adults (four women, six men) with a mean +/- SD age of 30.7 +/- 9.4 years.Intervention. All subjects received saquinavir 1200 mg 3 times/day with food on days 1-11 and quercetin 500 mg 3 times/day with food on days 4-11.Measurements and Main Results. On days 4 and 11, nine blood samples and four peripheral blood mononuclear cell samples were drawn during a steady-state dosing interval. Pharmacokinetic parameters were calculated by using standard noncompartmental techniques. Plasma saquinavir concentrations were similar regardless of quercetin administration. Geometric mean ratios for the area under the concentration-time curve during an 8-hour dosing interval (AUC(0-8)), maximum concentration in the dosing interval, and minimum concentration in the dosing interval were 0.99 (95% confidence interval [CI] 0.65-1.50), 0.99 (95% CI 0.64-1.54), and 1.06 (95% CI 0.68-1.67), respectively. Intracellular saquinavir concentrations displayed substantial intra- and intersubject variability, which limited the ability to determine the influence of quercetin coadministration (geometric mean ratio for AUC(0-8) = 0.51 [95% CI 0.14-1.95], six patients).Conclusion. Quercetin coadministration did not influence plasma saquinavir concentrations. Because of substantial inter- and intrasubject variability, more study is necessary to determine if saquinavir intracellular concentrations are altered by coadministration of quercetin.

OBJECTIVES The purpose of this study was to determine the pharmacokinetics and tolerability of three different indinavir and lopinavir/ritonavir dosing regimens. METHODS HIV-infected adults receiving lopinavir/ritonavir 400/100 mg twice daily with food had nine plasma samples taken over a 12 h dosing interval at baseline (BL), after adding indinavir 600 mg twice daily for 10 days (R1), indinavir 800 mg twice daily for 5 days (R2) and lopinavir/ritonavir 533/133 mg plus indinavir 600 mg twice daily for 10 days (R3). Plasma samples were assayed using HPLC. RESULTS A total of 12 patients completed the BL visit [10 male; mean (SD) age=43.9 (5.8) years] and 9, 7 and 7 completed R1, R2 and R3 visits, respectively. Two subjects discontinued treatment due to hypertriglyceridaemia. Compared with BL, the R3 lopinavir AUC (P<0.05) and Cmin (P=0.0025) were significantly higher and the R2 AUC trended higher (P=0.09). The indinavir AUC (P=0.030) and Cmax (P=0.035) were significantly higher for R2 compared with R1. There was a trend for increased total bilirubin (TB) after the addition of indinavir (P=0.09). Lopinavir and indinavir AUC, Cmax and Cmin were associated with TB during univariate analyses (P<0.01) while only lopinavir AUC (P=0.0004) and indinavir AUC (P=0.0028) were associated with TB during multivariate analysis. Only indinavir AUC was significant when both drugs were included in the model (P=0.0028). CONCLUSIONS Elevated lopinavir and indinavir concentrations are associated with elevated TB.

Background: New indications for misoprostol include medical abortion, cervical softening, induction of labor and treatment of postpartum hemorrhage. Various routes of misoprostol administration under study include oral, vaginal, buccal, sublingual and rectal.Materials and Methods: This was an open-label, randomized, cross-over study of the pharmacokinetic differences of buccal vs. sublingual misoprostol 800 mug in 10 healthy women.Results: Of the 10 women enrolled, 2 withdrew after experiencing excessive cramping from the sublingual route of misoprostol. The mean misoprostol plasma concentration-time curves at 4 h [area under the curve (AUC)(0-4))] and the maximum concentration (C-max) showed that levels were significantly higher for sublingual administration than the buccal route. Buccal misoprostol administration resulted in fewer symptoms and was found to be more acceptable.Conclusions: Sublingual administration of misoprostol had a higher AUC and C-max compared with buccal administration. The pharmacokinetics may help to determine the best application of misoprostol depending on the indication. (C) 2005 Elsevier Inc. All rights reserved.

Delavirdine is a non-nucleoside reverse transcriptase inhibitor used in combination regimens for the treatment of HIV-1 infection. Our objective was to characterise the population pharmacokinetics of delavirdine in HIV-infected patients who participated in the adult AIDS Clinical Trials Group (ACTG) 260 and 261 studies.

Background/Aims Indinavir (IDV) is metabolized mainly by hepatic CYP450, primarily CYP3A4. It has been reported that efavirenz (EFV) induces CYP3A4, while nelfinavir (NFV) inhibits its activity. Therefore, pharmacokinetic (PK) interactions between IDV and EFV / NFV are expected. The goal of this PK analysis was to explore the differences observed in IDV PK among treatment arms (ARM 1: IDV alone; ARM 2: IDV+ EFV; ARM3: IDV+ NFV) in clinical trial ACTG 388. Methods Three hundred fifty-two patients provided a total of 987 IDV concentration measurements. These were drawn at week 2 (12 (8) h PK study for ARM3 (1), approximately 10 (8) samples/study; 18 patients) and at week 40 (12h PK study for arm 3, approximately 10 samples/study; 7 patients). An additional random (“population”) sample was drawn at one or more follow-up visits in 347 patients. A two-compartment PK disposition model with first order absorption and “well stirred” hepatic elimination was fit to the concentration data. Results The oral clearance (CL/F) of IDV was 49.9 L/h. IDV CL/F was significantly increased with co-administration of EFV (45%), while NFV reduced IDV CL/F by 26%. Patient weight was associated with a marginal increase of IDV CL/F (5% higher CL/F/10 Kg; p<0.05). Neither gender, age, race, nor height were correlated with IDV CL/F. Conclusion These data extend our previous population analysis and show that IDV CL/F is higher and lower when combined with EFV and NFV, respectively. Clinical Pharmacology & Therapeutics (2005) 77, P80–P80; doi: 10.1016/j.clpt.2004.12.199

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a diverse group of compounds that inhibit HIV Type 1 reverse transcriptase. Although possessing a common mechanism of action, the approved NNRTIs, delavirdine, efavirenz and nevirapine, differ in structural and pharmacokinetic characteristics. Each of the NNRTIs undergoes biotransformation by the cytochrome P450 (CYP) enzyme system, thus making them prone to clinically significant drug interactions when combined with other antiretrovirals. In addition, they interact with other concurrent medications and complementary/alternative medicines, acting as either inducers or inhibitors of drug-metabolising CYP enzymes. These drug interactions become an important consideration in the clinical use of these agents when designing combination regimens, as recommended by current guidelines. This review provides an updated summary of pharmacokinetic interactions with NNRTIs.