PBPK-led assessment of antimalarial drugs as candidates for Covid-19: Simulating concentrations at the site of action to inform repurposing strategies.

The urgent need for safe, efficacious, and accessible drug treatments to treat coronavirus disease 2019 (COVID-19) prompted a global effort to evaluate drug repurposing opportunities. Pyronaridine and amodiaquine are both components of approved antimalarials with in vitro activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In vitro activity does not always translate to clinical efficacy across a therapeutic dose range. This study applied available, verified, physiologically based pharmacokinetic (PBPK) models for pyronaridine, amodiaquine, and its active metabolite N-desethylamodiaquine (DEAQ) to predict drug concentrations in lung tissue relative to plasma or blood in the default healthy virtual population. Lung exposures were compared to published data across the reported range of in vitro EC50 values against SARS-CoV-2. In the multicompartment permeability-limited PBPK model, the predicted total Cmax in lung mass for pyronaridine was 34.2 µM on Day 3, 30.5-fold greater than in blood (1.12 µM) and for amodiaquine was 0.530 µM, 8.83-fold greater than in plasma (0.060 µM). In the perfusion-limited PBPK model, the DEAQ predicted total Cmax on Day 3 in lung mass (30.2 µM) was 21.4-fold greater than for plasma (1.41 µM). Based on the available in vitro data, predicted drug concentrations in lung tissue for pyronaridine and DEAQ, but not amodiaquine, appeared sufficient to inhibit SARS-CoV-2 replication. Simulations indicated standard dosing regimens of pyronaridine-artesunate and artesunate-amodiaquine have potential to treat COVID-19. These findings informed repurposing strategies to select the most relevant compounds for clinical investigation in COVID-19. Clinical data for model verification may become available from ongoing clinical studies.

Supplementing clinical lactation studies with PBPK modeling to inform drug therapy in lactating mothers: Prediction of primaquine exposure as a case example.

Evaluating the safety of primaquine (PQ) during breastfeeding requires an understanding of its pharmacokinetics (PKs) in breast milk and its exposure in the breastfed infant. Physiologically-based PK (PBPK) modeling is primed to assess the complex interplay of factors affecting the exposure of PQ in both the mother and the nursing infant. A published PBPK model for PQ describing the metabolism by monoamine oxidase A (MAO-A; 90% contribution) and cytochrome P450 2D6 (CYP2D6; 10%) in adults was applied to predict the exposure of PQ in mothers and their breastfeeding infants. Plasma exposures following oral daily dosing of 0.5 mg/kg in the nursing mothers in a clinical lactation study were accurately captured, including the observed ranges. Reported infant daily doses based on milk data from the clinical study were used to predict the exposure of PQ in breastfeeding infants greater than or equal to 28 days. On average, the predicted exposures were less than or equal to 0.13% of the mothers. Furthermore, in simulations involving neonates less than 28 days, PQ exposures remain less than 0.16% of the mothers. Assuming that MAO-A increases slowly with age, the predicted relative exposure of PQ remains low in neonates (<0.46%). Thus, the findings of our study support the recommendation made by the authors who reported the results of the clinical lactation study, that is, that when put into context of safety data currently available in children, PQ should not be withheld in lactating women as it is unlikely to cause adverse events in breastfeeding infants greater than or equal to 28 days old.

Development and application of a PBPK modeling strategy to support antimalarial drug development.

As part of a collaboration between Medicines for Malaria Venture (MMV), Certara UK and Monash University, physiologically-based pharmacokinetic (PBPK) models were developed for 20 antimalarials, using data obtained from standardized in vitro assays and clinical studies within the literature. The models have been applied within antimalarial drug development at MMV for more than 5 years. During this time, a strategy for their impactful use has evolved. All models are described in the supplementary material and are available to researchers. Case studies are also presented, demonstrating real-world development and clinical applications, including the assessment of the drug-drug interaction liability between combination partners or with co-administered drugs. This work emphasizes the benefit of PBPK modeling for antimalarial drug development and decision making, and presents a strategy to integrate it into the research and development process. It also provides a repository of shared information to benefit the global health research community.

Safety of elexacaftor/tezacaftor/ivacaftor dose reduction: Mechanistic exploration through physiologically based pharmacokinetic modeling and a clinical case series.

INTRODUCTION: Elexacaftor/tezacaftor/ivacaftor (ETI) treatment is associated with significant improvement in lung function in people with cystic fibrosis (pwCF); however, some patients experience adverse effects (AEs) including hepatotoxicity. One potential strategy is dose reduction in ETI with the goal of maintaining therapeutic efficacy while resolving AEs. We report our experience of dose reduction in individuals who experienced AEs following ETI therapy. We provide mechanistic support for ETI dose reduction by exploring predicted lung exposures and underlying pharmacokinetics-pharmacodynamics (PK-PD) relationships. METHOD: Adults prescribed ETI who underwent dose reduction due to the AEs were included in this case series, and their percent predicted forced expiratory volume in 1 s (ppFEV1 ) and self-reported respiratory symptoms were collected. The full physiologically based pharmacokinetic (PBPK) models of ETI were developed incorporating physiological information and drug-dependent parameters. The models were validated against available pharmacokinetic and dose-response relationship data. The models were then used to predict lung concentrations of ETI at steady-state. RESULTS: Fifteen patients underwent dose reduction in ETI due to AEs. Clinical stability without significant changes in ppFEV1 after dose reduction was observed in all patients. Resolution or improvement of AEs occurred in 13 of the 15 cases. The model-predicted lung concentrations of reduced dose ETI exceeded the reported half maximal effective concentration (EC50 ) from measurement of in vitro chloride transport, providing a hypothesis as to why therapeutic efficacy was maintained. CONCLUSION: Albeit in a small number of patients, this study provides evidence that reduced ETI doses in pwCF who have experienced AEs may be effective. The PBPK models enable exploration of a mechanistic basis for this finding by simulating target tissue concentrations of ETI that can be compared with drug efficacy in vitro.

Physiologically-Based Pharmacokinetic-Led Guidance for Patients With Cystic Fibrosis Taking Elexacaftor-Tezacaftor-Ivacaftor With Nirmatrelvir-Ritonavir for the Treatment of COVID-19.

Cystic fibrosis transmembrane conductance regulator (CFTR) modulating therapies, including elexacaftor-tezacaftor-ivacaftor, are primarily eliminated through cytochrome P450 (CYP) 3A-mediated metabolism. This creates a therapeutic challenge to the treatment of coronavirus disease 2019 (COVID-19) with nirmatrelvir-ritonavir in people with cystic fibrosis (CF) due to the potential for significant drug-drug interactions (DDIs). However, the population with CF is more at risk of serious illness following COVID-19 infection and hence it is important to manage the DDI risk and provide treatment options. CYP3A-mediated DDI of elexacaftor-tezacaftor-ivacaftor was evaluated using a physiologically-based pharmacokinetic modeling approach. Modeling was performed incorporating physiological information and drug-dependent parameters of elexacaftor-tezacaftor-ivacaftor to predict the effect of ritonavir (the CYP3A inhibiting component of the combination) on the pharmacokinetics of elexacaftor-tezacaftor-ivacaftor. The elexacaftor-tezacaftor-ivacaftor models were verified using independent clinical pharmacokinetic and DDI data of elexacaftor-tezacaftor-ivacaftor with a range of CYP3A modulators. When ritonavir was administered on Days 1 through 5, the predicted area under the curve (AUC) ratio of ivacaftor (the most sensitive CYP3A substrate) on Day 6 was 9.31, indicating that its metabolism was strongly inhibited. Based on the predicted DDI, the dose of elexacaftor-tezacaftor-ivacaftor should be reduced when coadministered with nirmatrelvir-ritonavir to elexacaftor 200 mg-tezacaftor 100 mg-ivacaftor 150 mg on Days 1 and 5, with delayed resumption of full-dose elexacaftor-tezacaftor-ivacaftor on Day 9, considering the residual inhibitory effect of ritonavir as a mechanism-based inhibitor. The simulation predicts a regimen of elexacaftor-tezacaftor-ivacaftor administered concomitantly with nirmatrelvir-ritonavir in people with CF that will likely decrease the impact of the drug interaction.

Development of physiologically-based pharmacokinetic models for standard of care and newer tuberculosis drugs.

Tuberculosis (TB) remains a global health problem and there is an ongoing effort to develop more effective therapies and new combination regimes that can reduce duration of treatment. The purpose of this study was to demonstrate utility of a physiologically-based pharmacokinetic modeling approach to predict plasma and lung concentrations of 11 compounds used or under development as TB therapies (bedaquiline [and N-desmethyl bedaquiline], clofazimine, cycloserine, ethambutol, ethionamide, isoniazid, kanamycin, linezolid, pyrazinamide, rifampicin, and rifapentine). Model accuracy was assessed by comparison of simulated plasma pharmacokinetic parameters with healthy volunteer data for compounds administered alone or in combination. Eighty-four percent (area under the curve [AUC]) and 91% (maximum concentration [Cmax ]) of simulated mean values were within 1.5-fold of the observed data and the simulated drug-drug interaction ratios were within 1.5-fold (AUC) and twofold (Cmax ) of the observed data for nine (AUC) and eight (Cmax ) of the 10 cases. Following satisfactory recovery of plasma concentrations in healthy volunteers, model accuracy was assessed further (where patients' with TB data were available) by comparing clinical data with simulated lung concentrations (9 compounds) and simulated lung: plasma concentration ratios (7 compounds). The 5th-95th percentiles for the simulated lung concentration data recovered between 13% (isoniazid and pyrazinamide) and 88% (pyrazinamide) of the observed data points (Am J Respir Crit Care Med, 198, 2018, 1208; Nat Med, 21, 2015, 1223; PLoS Med, 16, 2019, e1002773). The impact of uncertain model parameters, such as the fraction of drug unbound in lung tissue mass (fumass ), is discussed. Additionally, the variability associated with the patient lung concentration data, which was sparse and included extensive within-subject, interlaboratory, and experimental variability (as well interindividual variability) is reviewed. All presented models are transparently documented and are available as open-source to aid further research.

Impact of Disease on Plasma and Lung Exposure of Chloroquine, Hydroxychloroquine and Azithromycin: Application of PBPK Modeling.

We use a mechanistic lung model to demonstrate that accumulation of chloroquine (CQ), hydroxychloroquine (HCQ), and azithromycin (AZ) in the lungs is sensitive to changes in lung pH, a parameter that can be affected in patients with coronavirus disease 2019 (COVID-19). A reduction in pH from 6.7 to 6 in the lungs, as observed in respiratory disease, led to 20-fold, 4.0-fold, and 2.7-fold increases in lung exposure of CQ, HCQ, and AZ, respectively. Simulations indicated that the relatively high concentrations of CQ and HCQ in lung tissue were sustained long after administration of the drugs had stopped. Patients with COVID-19 often present with kidney failure. Our simulations indicate that renal impairment (plus lung pH reduction) caused 30-fold, 8.0-fold, and 3.4-fold increases in lung exposures for CQ, HCQ, and AZ, respectively, with relatively small accompanying increases (20 to 30%) in systemic exposure. Although a number of different dosage regimens were assessed, the purpose of our study was not to provide recommendations for a dosing strategy, but to demonstrate the utility of a physiologically-based pharmacokinetic modeling approach to estimate lung concentrations. This, used in conjunction with robust in vitro and clinical data, can help in the assessment of COVID-19 therapeutics going forward.

An in vitro toolbox to accelerate anti-malarial drug discovery and development.

BACKGROUND: Modelling and simulation are being increasingly utilized to support the discovery and development of new anti-malarial drugs. These approaches require reliable in vitro data for physicochemical properties, permeability, binding, intrinsic clearance and cytochrome P450 inhibition. This work was conducted to generate an in vitro data toolbox using standardized methods for a set of 45 anti-malarial drugs and to assess changes in physicochemical properties in relation to changing target product and candidate profiles. METHODS: Ionization constants were determined by potentiometric titration and partition coefficients were measured using a shake-flask method. Solubility was assessed in biorelevant media and permeability coefficients and efflux ratios were determined using Caco-2 cell monolayers. Binding to plasma and media proteins was measured using either ultracentrifugation or rapid equilibrium dialysis. Metabolic stability and cytochrome P450 inhibition were assessed using human liver microsomes. Sample analysis was conducted by LC-MS/MS. RESULTS: Both solubility and fraction unbound decreased, and permeability and unbound intrinsic clearance increased, with increasing Log D7.4. In general, development compounds were somewhat more lipophilic than legacy drugs. For many compounds, permeability and protein binding were challenging to assess and both required the use of experimental conditions that minimized the impact of non-specific binding. Intrinsic clearance in human liver microsomes was varied across the data set and several compounds exhibited no measurable substrate loss under the conditions used. Inhibition of cytochrome P450 enzymes was minimal for most compounds. CONCLUSIONS: This is the first data set to describe in vitro properties for 45 legacy and development anti-malarial drugs. The studies identified several practical methodological issues common to many of the more lipophilic compounds and highlighted areas which require more work to customize experimental conditions for compounds being designed to meet the new target product profiles. The dataset will be a valuable tool for malaria researchers aiming to develop PBPK models for the prediction of human PK properties and/or drug-drug interactions. Furthermore, generation of this comprehensive data set within a single laboratory allows direct comparison of properties across a large dataset and evaluation of changing property trends that have occurred over time with changing target product and candidate profiles.

Derivation of CYP3A4 and CYP2B6 degradation rate constants in primary human hepatocytes: A siRNA-silencing-based approach.

The first-order degradation rate constant (kdeg) of cytochrome P450 (CYP) enzymes is a known source of uncertainty in the prediction of time-dependent drug-drug interactions (DDIs) in physiologically-based pharmacokinetic (PBPK) modelling. This study aimed to measure CYP kdeg using siRNA to suppress CYP expression in primary human hepatocytes followed by incubation over a time-course and tracking of protein expression and activity to observe degradation. The magnitude of gene knockdown was determined by qPCR and activity was measured by probe substrate metabolite formation and CYP2B6-Glo™ assay. Protein disappearance was determined by Western blotting. During a time-course of 96 and 60 h of incubation, over 60% and 76% mRNA knockdown was observed for CYP3A4 and CYP2B6, respectively. The kdeg of CYP3A4 and CYP2B6 protein was 0.0138 h-1 (±0.0023) and 0.0375 h-1 (±0.025), respectively. The kdeg derived from probe substrate metabolism activity was 0.0171 h-1 (±0.0025) for CYP3A4 and 0.0258 h-1 (±0.0093) for CYP2B6. The CYP3A4 kdeg values derived from protein disappearance and metabolic activity were in relatively good agreement with each other and similar to published values. This novel approach can now be used for other less well-characterised CYPs.

Incompatibility of chemical protein synthesis inhibitors with accurate measurement of extended protein degradation rates.

Protein synthesis inhibitors are commonly used for measuring protein degradation rates, but may cause cytotoxicity via direct or indirect mechanisms. This study aimed to identify concentrations providing optimal inhibition in the absence of overt cytotoxicity. Actinomycin D, cycloheximide, emetine, and puromycin were assessed individually, and in two-, three-, and four-drug combinations for protein synthesis inhibition (IC50 ) and cytotoxicity (CC50 ) over 72 h. Experiments were conducted in HepG2 cells and primary rat hepatocytes (PRH). IC50 for actinomycin D, cycloheximide, emetine, and puromycin were 39 ± 7.4, 6600 ± 2500, 2200 ± 1400, and 1600 ± 1200 nmol/L; with corresponding CC50 values of 6.2 ± 7.3, 570 ± 510, 81 ± 9, and 1300 ± 64 nmol/L, respectively, in HepG2 cells. The IC50 were 1.7 ± 1.8, 290 ± 90, 620 ± 920, and 2000 ± 2000 nmol/L, with corresponding CC50 values of 0.98 ± 1.8, 680 ± 1300, 180 ± 700, and 1600 ± 1000 (SD) nmol/L, respectively, in PRH. CC50 were also lower than the IC50 for all drug combinations in HepG2 cells. These data indicate that using pharmacological interference is inappropriate for measuring protein degradation over a protracted period, because inhibitory effects cannot be extricated from cytotoxicity.

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.

Incorporating population variability and susceptible subpopulations into dosimetry for high-throughput toxicity testing.

Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assessment context. Previously, we employed in vitro hepatic metabolic clearance and plasma protein binding data with in vitro in vivo extrapolation (IVIVE) modeling to estimate oral equivalent doses, or daily oral chemical doses required to achieve steady-state blood concentrations (Css) equivalent to media concentrations having a defined effect in an in vitro HTS assay. In this study, hepatic clearance rates of selected ToxCast chemicals were measured in vitro for 13 cytochrome P450 and five uridine 5'-diphospho-glucuronysyltransferase isozymes using recombinantly expressed enzymes. The isozyme-specific clearance rates were then incorporated into an IVIVE model that captures known differences in isozyme expression across several life stages and ethnic populations. Comparison of the median Css for a healthy population against the median or the upper 95th percentile for more sensitive populations revealed differences of 1.3- to 4.3-fold or 3.1- to 13.1-fold, respectively. Such values may be used to derive chemical-specific human toxicokinetic adjustment factors. The IVIVE model was also used to estimate subpopulation-specific oral equivalent doses that were directly compared with subpopulation-specific exposure estimates. This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability. Incorporation of these values with dosimetry and in vitro bioactivities provides a viable approach that could be employed within a high-throughput risk assessment framework.

Prediction of drug-drug interactions between various antidepressants and efavirenz or boosted protease inhibitors using a physiologically based pharmacokinetic modelling approach.

BACKGROUND AND OBJECTIVE: The 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. METHODS: In 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. RESULTS: Simulated 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. CONCLUSION: The 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.

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.

Intracellular and plasma pharmacokinetics of efavirenz in HIV-infected individuals.

OBJECTIVES: The site of action of efavirenz is inside HIV-infected cells. Measurement of intracellular (IC) concentrations of efavirenz may therefore provide further understanding of therapeutic failure, especially where virological rebound occurs despite adequate plasma levels, and a lack of detectable viral resistance. Here, we determined IC and plasma pharmacokinetics of efavirenz and their relationship with plasma protein binding and P-glycoprotein (P-gp, an active drug efflux transporter) expression. PATIENTS AND METHODS: Venous blood samples from 10 HIV-infected patients receiving efavirenz (600 mg once a day plus two nucleoside reverse transcriptase inhibitors) were collected over the 24 h dosing interval. Plasma and peripheral blood mononuclear cells (PBMCs) were isolated. Plasma protein bound and unbound efavirenz were separated using ultrafiltration. IC (or cell-associated), total plasma and unbound plasma efavirenz levels were quantified using HPLC-UV. P-gp expression was measured by flow cytometry. Area under the concentration-time curves (AUC0-24) were then calculated using non-compartmental analyses and the IC accumulation expressed as a ratio of IC to plasma AUC0-24. RESULTS: The median (range) % unbound and IC accumulation ratio was 0.6% (0.4-1.5%) and 1.3 (0.7-3.3), respectively. There was a linear relationship between IC and total AUC0-24 (r2= 0.59, P = 0.01) but not unbound AUC0-24 (r2= 0.13, P = 0.75). An inverse correlation between IC AUC0-24 and % unbound was observed (r2= 41, P = 0.05). There was no relationship between IC AUC0-24 and P-gp expression on the cell surface (r2< 0.01, P = 0.98). CONCLUSIONS: There was a direct relationship between % bound efavirenz in plasma and IC accumulation implying that the IC accumulation of efavirenz is related to binding to IC proteins or other cellular constituents. Studies investigating the unbound concentration of antiretrovirals inside the cell are now required.

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

BACKGROUND AND OBJECTIVE: 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. METHODS: Plasma and peripheral blood mononuclear cells were isolated from blood samples taken from 10 HIV-infected patients at 0, 2, 4, 8, and 12 hours after dosing. Intracellular and plasma (total and unbound) concentrations were determined by liquid chromatography-tandem mass spectrometry, and the ratios of intracellular to total plasma exposure (area under the concentration-time curves) were calculated. P-gp expression was measured by flow cytometry. RESULTS: The median intracellular accumulation ratio was 0.005 (range, 0.001-0.054) and remained unchanged over the dosing interval. There was an association between higher plasma concentrations and lower cellular concentrations of nevirapine (total r(2) = 0.62, P = .007). There was no relationship between percent unbound nevirapine and intracellular nevirapine. There was a correlation between higher plasma nevirapine exposure and higher P-gp expression (r(2) = 0.77, P = .03), whereas intracellular nevirapine exposure decreased with higher P-gp expression (r(2) = 0.62, P = .01). CONCLUSIONS: The intracellular accumulation of nevirapine was low, did not change over the dosing interval, and was not related to protein binding. In this small study, cells with higher P-gp expression had lower cellular concentrations of nevirapine. Further studies are required to explore the influx and efflux transporter profile of this drug.

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.

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.

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.