Lisa M. Almond

The effects of protease inhibitors and nonnucleoside reverse transcriptase inhibitors on p-glycoprotein expression in peripheral blood mononuclear cells in vitro.

Several antiretroviral compounds have been shown to be substrates for the efflux protein P-glycoprotein (P-gp) although few studies have investigated the effects of drug on expression of this protein. Here, an in vitro system has been adopted to investigate the effects of protease inhibitors (PIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs) on P-gp expression in peripheral blood mononuclear cells (PBMCs). PBMCs isolated from healthy volunteers were incubated with 10 or 100 microM PI (saquinavir, ritonavir, lopinavir, indinavir, nelfinavir, amprenavir) or 10 microM NNRTI (efavirenz, nevirapine) for 72 hours. Surface P-gp expression was measured by flow cytometry and compared with vehicle-incubated controls. Toxicity was assessed by MTT assay and the effects of each compound were compared between individuals with differing genotypes at position 3435 of exon 26 of MDR1, which was assigned by restriction fragment length polymorphism. Significant increases in median P-gp expression were observed following incubation with 10 microM nelfinavir (10.2 versus 6.7% P-gp-positive cells) and efavirenz (10.0 versus 6.7% P-gp-positive cells). No significant differences in induction were observed between genotypes (CC, CT, TT). Following incubation with 100 microM PI, significant upregulation of P-gp occurred except with amprenavir. However, nelfinavir, ritonavir, and lopinavir caused marked toxicity, indicating that at higher concentrations, the increase in P-gp may be at least partially related to a stress response. These results indicate the potential of some PIs and NNRTIs to induce P-gp expression in PBMCs in vitro.

Intracellular and plasma pharmacokinetics of nevirapine in human immunodeficiency virus-infected individuals.

Plasma concentrations of nevirapine have been linked to human immunodeficiency virus (HIV) treatment outcome. However, because the site of action of nevirapine is within HIV‐infected cells, intracellular concentrations may better relate to antiviral exposure. Investigation of factors that alter the intracellular pharmacokinetics of nevirapine may also aid in our understanding of therapeutic failure. Our objective was to determine intracellular (or cell‐associated) nevirapine concentrations over the full dosing interval and to relate protein binding and P‐glycoprotein (P‐gp) expression to intracellular exposure.

The Relationship between Nevirapine Plasma Concentrations and Abnormal Liver Function Tests

Abnormal liver function tests are frequently observed in HIV-infected individuals receiving nevirapine (NVP). Here we investigate the relationship between total and unbound plasma concentrations of NVP and the liver enzymes alanine aminotransferase (ALT) and gamma-glutamyl transferase (gammaGT). HIV-infected individuals [n = 85, 22 female, 34 hepatitis C or B virus (HCV or HBV(+))] receiving NVP (200 mg bd; median duration 66 weeks, range 3-189) and two nucleoside reverse transcriptase inhibitors (NRTIs) were enrolled into this study. Blood samples were taken at C(trough) (12 hr postdose) for measurement of NVP and liver function tests (ALT and gammaGT). Plasma protein bound and unbound drug was separated using ultrafiltration and NVP concentrations quantified using HPLC-MS/MS. A linear relationship was observed between total and unbound NVP C(trough) (r(2) = 0.77, p < 0.0001). Patients with elevated ALT (>37 IU/liter; n = 31) had higher NVP unbound C(trough) than those with ALT within the normal range (median 2268 vs. 1694 ng/ml, p = 0.04) but there was no difference in total C(trough). Logistic regression revealed no association between higher NVP C(trough) and ALT elevations. Significantly higher NVP total and unbound C(trough) were observed in patients with increased gammaGT (>40 IU/liter; n = 63; total 6747 vs. 4530 ng/ml, p = 0.001; unbound 2113 vs. 1557 ng/ml, p = 0.03). Significantly higher unbound NVP C(trough) was observed in HCV/HBV(+) (median 2275 vs. 1726 ng/ml, p = 0.02) and on bivariate analysis, higher NVP C(trough) was associated with HCV/HBV coinfection (chi(2) = 4.228; p = 0.04). Overall we found no strong association between NVP concentrations and hepatotoxicity. Although in this study NVP was well tolerated in HCV/HBV coinfected patients, higher plasma concentrations were observed.

Application of a systems approach to the bottom-up assessment of pharmacokinetics in obese patients: Expected variations in clearance

Background and Objectives: The maintenance dose of a drug is dependent on drug clearance, and thus any biochemical and physiological changes in obesity that affect parameters such as cardiac output, renal function, expression of drug-metabolizing enzymes and protein binding may result in altered clearance compared with that observed in normal-weight subjects (corrected or uncorrected for body weight). Because of the increasing worldwide incidence of obesity, there is a need for more information regarding the optimal dosing of drug therapy to be made available to prescribers. This is usually provided via clinical studies in obese people; however, such studies are not available for all drugs that might be used in obese subjects. Incorporation of the relevant physiological and biochemical changes into predictive bottom-up pharmacokinetic models in order to optimize dosage regimens may offer a logical way forward for the cases where no clinical data exist. The aims of the current report are to apply such a ‘systems approach’ to identify the likelihood of observing variations in the clearance of drugs in obesity and morbid obesity for a set of compounds for which clinical data, as well as the necessary in vitro information, are available, and to provide a framework for assessing other drugs in the future.Methods: The population-specific changes in demographic, physiological and biochemical parameters that are known to be relevant to obese and morbidly obese subjects were collated and incorporated into two separate population libraries. These libraries, together with mechanistic in vitro-in vivo extrapolations (IVIVE) within the Simcyp Population-based Simulator™, were used to predict the clearance of oral alprazolam, oral caffeine, oral chlorzoxazone, oral ciclosporin, intravenous and oral midazolam, intravenous phenytoin, oral theophylline and oral triazolam. The design of the simulated studies was matched as closely as possible with that of the clinical studies. Outcome was measured by the predicted ratio of the clearance of the drug in obese and lean subjects ± its 90% confidence interval, compared with observed values. The overall statistical measures of the performance of the model to detect differences in compound clearance between obese and lean populations were investigated by measuring sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). A power calculation was carried out to investigate the impact of the sample size on the overall outcome of clinical studies.Results: The model was successful in predicting clearance in obese subjects, with the degree to which simulations could mimic the outcome of in vivo studies being greater than 60% for six of the eight drugs. A clear difference in the clearance of chlorzoxazone was correctly picked up via simulation. The overall statistical measures of the performance of the Simcyp Simulator were 100% sensitivity, 66% specificity, 60% PPV and 100% NPV. Studies designed on the basis of the ratio of the absolute values required substantial numbers of participants in order to detect a significant difference, except for phenytoin and chlorzoxazone, where the ratios of the weight-normalized clearances generally showed statistically significant differences with a smaller number of subjects.Conclusion: Extension of a mechanistic predictive pharmacokinetic model to accommodate physiological and biochemical changes associated with obesity and morbid obesity allowed prediction of changes in drug clearance on the basis of in vitro data, with reasonable accuracy across a range of compounds that are metabolized by different enzymes. Prediction of the effects of obesity on drug clearance, normalized by various body size scalars, is of potential value in the design of clinical studies during drug development and in the introduction of dosage adjustments that are likely to be needed in clinical practice.

Pharmacokinetic and Pharmacodynamic Analysis of Efavirenz Dose Reduction Using an In Vitro–In Vivo Extrapolation Model

The pharmacokinetics (PK) of efavirenz (EFV) is characterized by marked interpatient variability that correlates with its pharmacodynamics (PD). In vitro–in vivo extrapolation (IVIVE) is a “bottom‐up” approach that combines drug data with system information to predict PK and PD. The aim of this study was to simulate EFV PK and PD after dose reductions. At the standard dose, the simulated probability was 80% for viral suppression and 28% for central nervous system (CNS) toxicity. After a dose reduction to 400 mg, the probabilities of viral suppression were reduced to 69, 75, and 82%, and those of CNS toxicity were 21, 24, and 29% for the 516 GG, 516 GT, and 516 TT genotypes, respectively. With reduction of the dose to 200 mg, the probabilities of viral suppression decreased to 54, 62, and 72% and those of CNS toxicity decreased to 13, 18, and 20% for the 516 GG, 516 GT, and 516 TT genotypes, respectively. These findings indicate how dose reductions might be applied in patients with favorable genetic characteristics.

A Physiologically Based Pharmacokinetic Modeling Approach to Predict Disease–Drug Interactions: Suppression of CYP3A by IL‐6

Elevated cytokine levels are known to downregulate expression and suppress activity of cytochrome P450 enzymes (CYPs). Cytokine‐modulating therapeutic proteins (TPs) used in the treatment of inflammation or infection could reverse suppression, manifesting as TP‐drug–drug interactions (TP‐DDIs). A physiologically based pharmacokinetic model was used to quantitatively predict the impact of interleukin‐6 (IL‐6) on sensitive CYP3A4 substrates. Elevated simvastatin area under the plasma concentration–time curve (AUC) in virtual rheumatoid arthritis (RA) patients, following 100 pg/ml of IL‐6, was comparable to observed clinical data (59 vs. 58%). In virtual bone marrow transplant (BMT) patients, 500 pg/ml of IL‐6 resulted in an increase in cyclosporine AUC, also in good agreement with the observed data (45 vs. 39%). In a different group of BMT patients treated with cyclosporine, the magnitude of interaction with IL‐6 was underpredicted by threefold. The complexity of TP‐DDIs highlights underlying pathophysiological factors to be considered, but these simulations provide valuable first steps toward predicting TP‐DDI risk.

Prediction of drug-drug Interactions Between Various Antidepressants and Efavirenz or Boosted Protease Inhibitors Using a Physiologically Based Pharmacokinetic Modelling Approach

Background and ObjectiveThe rate of depression in patients with HIV is higher than in the general population. The use of antidepressants can have a beneficial effect, improving antiretroviral therapy adherence and consequently their efficacy and safety. Efavirenz and protease inhibitor boosted with ritonavir are major components of the antiretroviral therapy and are inducers and/or inhibitors of several cytochrome P450 (CYP) isoforms. Although antidepressants are prescribed to a significant proportion of patients treated with antiretrovirals, there are limited clinical data on drug-drug interactions. The aim of this study was to predict the magnitude of drug-drug interactions among efavirenz, boosted protease inhibitors and the most commonly prescribed antidepressants using an in vitro-in vivo extrapolation (IVIVE) model simulating virtual clinical trials.MethodsIn vitro data describing the chemical characteristics, and absorption, distribution, metabolism and elimination (ADME) properties of efavirenz, boosted protease inhibitors and the most commonly prescribed antidepressants were obtained from published literature or generated by standard methods. Pharmacokinetics and drug-drug interaction were simulated using the full physiologically based pharmacokinetic model implemented in the Simcyp™ ADME simulator. The robustness of our modeling approach was assessed by comparing the magnitude of simulated drug-drug interactions using probe drugs to that observed in clinical studies.ResultsSimulated pharmacokinetics and drug-drug interactions were in concordance with available clinical data. Although the simulated drug-drug interactions with antidepressants were overall weak to moderate according to the classification of the US FDA, fluoxetine and venlafaxine represent better candidates from a pharmacokinetic standpoint for patients on efavirenz and venlafaxine or citalopram for patients on boosted protease inhibitors.ConclusionThe modest magnitude of interaction could be explained by the fact that antidepressants are substrates of multiple isoforms and thus metabolism can still occur through CYPs that are weakly impacted by efavirenz or boosted protease inhibitors. These findings indicate that IVIVE is a useful tool for predicting drug-drug interactions and designing prospective clinical trials, giving insight into the variability of exposure, sample size and time-dependent induction or inhibition.

Metformin and cimetidine: Physiologically based pharmacokinetic modelling to investigate transporter mediated drug–drug interactions

Metformin is used as a probe for OCT2 mediated transport when investigating possible DDIs with new chemical entities. The aim of the current study was to investigate the ability of physiologically-based pharmacokinetic (PBPK) models to simulate the effects of OCT and MATE inhibition by cimetidine on metformin kinetics. PBPK models were developed, incorporating mechanistic kidney and liver sub-models for metformin (OCT and MATE substrate) and a mechanistic kidney sub-model for cimetidine. The models were used to simulate inhibition of the MATE1, MATE2-K, OCT1 and OCT2 mediated transport of metformin by cimetidine. Assuming competitive inhibition and using cimetidine Ki values determined in vitro, the predicted metformin AUC ratio was 1.0 compared to an observed value of 1.46. The observed AUC ratio could only be recovered with this model when the cimetidine Ki for OCT2 was decreased 1000-fold or the Kis for both OCT1 and OCT2 were decreased 500-fold. An alternative description of metformin renal transport by OCT1 and OCT2, incorporating electrochemical modulation of the rate of metformin uptake together with 8-18-fold decreases in cimetidine Kis for OCTs and MATEs, allowed recovery of the extent of the observed effect of cimetidine on metformin AUC. While the final PBPK model has limitations, it demonstrates the benefit of allowing for the complexities of passive permeability combined with active cellular uptake modulated by an electrochemical gradient and active efflux.

Prediction of Drug-Drug Interactions Arising from CYP3A induction Using a Physiologically Based Dynamic Model

Using physiologically based pharmacokinetic modeling, we predicted the magnitude of drug-drug interactions (DDIs) for studies with rifampicin and seven CYP3A4 probe substrates administered i.v. (10 studies) or orally (19 studies). The results showed a tendency to underpredict the DDI magnitude when the victim drug was administered orally. Possible sources of inaccuracy were investigated systematically to determine the most appropriate model refinement. When the maximal fold induction (Indmax) for rifampicin was increased (from 8 to 16) in both the liver and the gut, or when the Indmax was increased in the gut but not in liver, there was a decrease in bias and increased precision compared with the base model (Indmax = 8) [geometric mean fold error (GMFE) 2.12 vs. 1.48 and 1.77, respectively]. Induction parameters (mRNA and activity), determined for rifampicin, carbamazepine, phenytoin, and phenobarbital in hepatocytes from four donors, were then used to evaluate use of the refined rifampicin model for calibration. Calibration of mRNA and activity data for other inducers using the refined rifampicin model led to more accurate DDI predictions compared with the initial model (activity GMFE 1.49 vs. 1.68; mRNA GMFE 1.35 vs. 1.46), suggesting that robust in vivo reference values can be used to overcome interdonor and laboratory-to-laboratory variability. Use of uncalibrated data also performed well (GMFE 1.39 and 1.44 for activity and mRNA). As a result of experimental variability (i.e., in donors and protocols), it is prudent to fully characterize in vitro induction with prototypical inducers to give an understanding of how that particular system extrapolates to the in vivo situation when using an uncalibrated approach.

Time-dependent changes in HIV nucleoside analogue phosphorylation and the effect of hydroxyurea.

Background: Nucleoside analogues are activated to their triphosphates, which compete with endogenous deoxynucleoside triphosphate (dNTP) pools to inhibit HIV reverse transcriptase. Hydroxyurea has been administered with nucleoside analogues to modulate intracellular dNTP pools and thus the ratio of drug triphosphate : endogenous triphosphate. Objectives: To examine changes in drug activation over time and investigate the effects of hydroxyurea on intracellular phosphorylation of antiretroviral nucleoside analogues. Patients: A total of 229 HIV-infected individuals receiving abacavir, lamivudine and zidovudine were randomly assigned to receive or not nevirapine and hydroxyurea. Twenty-four patients were recruited to an observational substudy measuring intracellular drug triphosphate and dNTP concentrations at 0, 2, 6, 12, 24 and 48 weeks. Methods: Drugs were extracted from isolated peripheral blood mononuclear cells before analysis of endogenous dNTP and drug triphosphates by primer extension assays. Results: Twenty-two out of 24 patients were followed to completion of the substudy. Hydroxyurea had no demonstrable effect on endogenous dNTP or drug triphosphate levels at any timepoint. However, the ratio of zidovudine triphosphate to endogenous deoxythymidine triphosphate was significantly increased with hydroxyurea. A significant decrease in lamivudine triphosphate (3TCTP) and the 3TCTP : endogenous deoxycytidine triphosphate ratio was seen over 48 weeks. In five patients who failed therapy in the first 24 weeks, significantly reduced 3TCTP was seen. Conclusion: Hydroxyurea does not affect measurable pools of endogenous nucleosides in vivo. Decreased lamivudine phosphorylation over time may provide a novel pharmacological explanation for the mechanism of resistance to this drug.