Development and validation of a population pharmacokinetic model for ritonavir used as a booster or as an antiviral agent in HIV-1-infected patients

Metal-Promoted Heterocyclization: A Heterosynthetic Approach to Face a Pandemic Crisis

The outbreak of SARS-CoV-2 has drastically changed our everyday life and the life of scientists from all over the world. In the last year, the scientific community has faced this worldwide threat using any tool available in order to find an effective response. The recent formulation, production, and ongoing administration of vaccines represent a starting point in the battle against SARS-CoV-2, but they cannot be the only aid available. In this regard, the use of drugs capable to mitigate and fight the virus is a crucial aspect of the pharmacological strategy. Among the plethora of approved drugs, a consistent element is a heterocyclic framework inside its skeleton. Heterocycles have played a pivotal role for decades in the pharmaceutical industry due to their high bioactivity derived from anticancer, antiviral, and anti-inflammatory capabilities. In this context, the development of new performing and sustainable synthetic strategies to obtain heterocyclic molecules has become a key focus of scientists. In this review, we present the recent trends in metal-promoted heterocyclization, and we focus our attention on the construction of heterocycles associated with the skeleton of drugs targeting SARS-CoV-2 coronavirus.

Population pharmacokinetic modelling of the changes in atazanavir plasma clearance caused by ritonavir plasma concentrations in HIV-1 infected patients

AIMS

The aim of the present study was to develop a simultaneous population pharmacokinetic model for atazanavir (ATV) incorporating the effect of ritonavir (RTV) on clearance to predict ATV concentrations under different dosing regimens in HIV-1-infected patients.

METHODS

A Cross-sectional study was carried out in 83 HIV-1-infected adults taking ATV 400 mg or ATV 300 mg/RTV 100 mg once daily. Demographic and clinical characteristics were registered and blood samples collected to measure drug concentrations. A population pharmacokinetic model was constructed using nonlinear mixed-effects modelling and used to simulate six dosing scenarios.

RESULTS

The selected one-compartmental model described the pharmacokinetics of RTV and ATV simultaneously, showing exponential, direct inhibition of ATV clearance according to the RTV plasma concentration, which explained 17.5% of the variability. A mean RTV plasma concentration of 0.63 mg l-1 predicted an 18% decrease in ATV clearance. The percentages of patients with an end-of-dose-interval concentration of ATV below or above the minimum and maximum target concentrations of 0.15 mg l-1 and 0.85 mg l-1 favoured the selection of the simulated ATV/RTV once-daily regimens (ATV 400 mg, ATV 300 mg/RTV 100 mg, ATV 300 mg/RTV 50 mg, ATV 200/RTV 100 mg) over the unboosted twice-daily regimens (ATV 300 mg, ATV 200 mg).

CONCLUSIONS

A one-compartment simultaneous model can describe the pharmacokinetics of RTV and ATV, including the effect of RTV plasma concentrations on ATV clearance. This model is promising for predicting individuals' ATV concentrations in clinical scenarios, and supports further clinical trials of once-daily doses of ATV 300 mg/RTV 50 mg or ATV 200 mg/RTV 100 mg to confirm efficacy and safety.

Model-based evaluation of the pharmacokinetic differences between adults and children for lopinavir and ritonavir in combination with rifampicin

AIMS

Rifampicin profoundly reduces lopinavir concentrations. Doubled doses of lopinavir/ritonavir compensate for the effect of rifampicin in adults, but fail to provide adequate lopinavir concentrations in young children on rifampicin-based antituberculosis therapy. The objective of this study was to develop a population pharmacokinetic model describing the pharmacokinetic differences of lopinavir and ritonavir, with and without rifampicin, between children and adults.

METHODS

An integrated population pharmacokinetic model developed in nonmem 7 was used to describe the pharmacokinetics of lopinavir and ritonavir in 21 HIV infected adults, 39 HIV infected children and 35 HIV infected children with tuberculosis, who were established on lopinavir/ritonavir-based antiretroviral therapy with and without rifampicin-containing antituberculosis therapy.

RESULTS

The bioavailability of lopinavir was reduced by 25% in adults whereas children on antituberculosis treatment experienced a 59% reduction, an effect that was moderated by the dose of ritonavir. Conversely, rifampicin increased oral clearance of both lopinavir and ritonavir to a lesser extent in children than in adults. Rifampicin therapy in administered doses increased CL of lopinavir by 58% in adults and 48% in children, and CL of ritonavir by 34% and 22% for adults and children, respectively. In children, the absorption half-life of lopinavir and the mean transit time of ritonavir were lengthened, compared with those in adults.

CONCLUSIONS

The model characterized important differences between adults and children in the effect of rifampicin on the pharmacokinetics of lopinavir and ritonavir. As adult studies cannot reliably predict their magnitude in children, drug-drug interactions should be evaluated in paediatric patient populations.

Antiviral activity, pharmacokinetics, and safety of the HIV-1 protease inhibitor TMC310911, coadministered with ritonavir, in treatment-naive HIV-1-infected patients

OBJECTIVES

TMC310911 is a novel HIV type-1 (HIV-1) protease inhibitor with broad in vitro antiviral activity. In this phase 2a, open-label randomized study, the antiviral activity, pharmacokinetics, and safety and tolerability of ritonavir-boosted TMC310911 was assessed.

METHODS

In this study, treatment-naive HIV-1 patients (aged 18-60 years) received 1 of the 4 dosing regimens of TMC310911: 150 mg twice-daily (bid) (n = 8), 300 mg bid (n = 8), 75 mg bid (n = 9), or 300 mg once-daily (qd) (n = 8), for 14 days, all coadministered with 100 mg of ritonavir, as only antiretroviral therapy.

RESULTS

The mean change from baseline in HIV-1 RNA (log10 copies per milliliter; primary efficacy endpoint) was -1.30 (75 mg bid), -1.14 (150 mg bid), -1.07 (300 mg bid), and -1.06 (300 mg qd) on day 8 and -1.53 (75 mg bid), -1.79 (150 mg bid), -1.69 (300 mg bid), and -1.55 (300 mg qd) on day 15. At steady state (day 14), the mean maximum plasma concentration and mean area under the plasma concentration-time curve from 0 to 12 hours tended to increase dose proportionally for bid doses; TMC310911 daily exposures for the 300 mg qd treatment and 150 mg bid treatment were comparable. The most common (≥ 10%) treatment-emergent adverse events were fatigue (27.3%) and nausea (12.1%); no deaths or serious treatment-emergent adverse events were reported in this study.

CONCLUSIONS

Combination treatment with TMC310911 and ritonavir showed potent antiviral activity (>1.5 log10 copies/mL decrease in plasma HIV-1 RNA) at all evaluated doses, and treatment was generally safe and well tolerated.

Clinical pharmacokinetics of antiretroviral drugs in older persons

INTRODUCTION

Combination antiretroviral therapy has enabled HIV-infected persons to reach older ages in high numbers. Hepatic and renal changes that normally occur with advancing age occur earlier and with higher incidence in HIV-infected individuals. A limited number of prospective controlled studies have demonstrated small reductions (17 to 41%) in lopinavir, atazanavir and lamivudine clearance in older versus younger adults. A much larger number of retrospective studies in adults (age range ∼ 20 to 60 years), including all antiretroviral drugs, have evaluated age as a covariate for pharmacokinetics. Most studies did not detect substantial associations between drug exposures and age.

AREAS COVERED

This review summarizes antiretroviral drug pharmacokinetics in older persons. The authors review articles from PubMed (search terms: elderly, antiretroviral, pharmacokinetics) in addition to the bibliographies of those selected.

EXPERT OPINION

The evidence to date does not support major pharmacokinetic changes in adults between ∼ 20 and 60 years of age. However, additional prospective, well-controlled studies are needed in more persons > 60 years, including those with frailty and comorbidities, with assessment of unbound drug clearance, and incorporation of adherence, pharmacogenetics and concomitant medications. Until then, guidelines for drug-drug interactions and dosing in renal and hepatic impairment should be followed in older HIV-infected individuals.

Population-Based Assessments of Clinical Drug-Drug Interactions: Qualitative Indices or Quantitative Measures?

Population-based assessments of drug-drug interactions have become more common since the introduction and acceptance of the population pharmacokinetic approach. Unlike traditional methods, population-based studies provide clinically relevant results that can be applied directly to a target patient population. Furthermore, population-based studies do not demand the traditional requirements of intensive pharmacokinetic sampling, rigorous inpatient stays, or stringent assessment schedules. As such, the population-based approach can effectively be used to confirm known drug-drug interactions and further characterize anticipated interactions. A prospectively designed analysis can also reveal drug-drug interactions that might otherwise have gone undetected with traditional methods. Ultimately, these results could help to alleviate clinicians' concerns about using widely marketed drugs in combination therapies and also reduce patients' risk of experiencing unacceptable side effects. This article intends to provide a balanced overview of the population-based approach and its merits, drawbacks, and potential utility in the assessment of drug-drug interactions during clinical drug development.

Model-based approach to dose optimization of lopinavir/ritonavir when co-administered with rifampicin

AIMS

Rifampicin, a key component of antitubercular treatment, profoundly reduces lopinavir concentrations. The aim of this study was to develop an integrated population pharmacokinetic model accounting for the drug-drug interactions between lopinavir, ritonavir and rifampicin, and to evaluate optimal doses of lopinavir/ritonavir when co-administered with rifampicin.

METHODS

Steady-state pharmacokinetics of lopinavir and ritonavir were sequentially evaluated after the introduction of rifampicin and gradually escalating the dose in a cohort of 21 HIV-infected adults. Intensive pharmacokinetic sampling was performed after each dose adjustment following a morning dose administered after fasting overnight. A population pharmacokinetic analysis was conducted using NONMEM 7.

RESULTS

A simultaneous integrated model was built. Rifampicin reduced the oral bioavailability of lopinavir and ritonavir by 20% and 45% respectively, and it increased their clearance by 71% and 36% respectively. With increasing concentrations of ritonavir, clearance of lopinavir decreased in an E(max) relationship. Bioavailability was 42% and 45% higher for evening doses compared with morning doses for lopinavir and ritonavir, respectively, while oral clearance of both drugs was 33% lower overnight. Simulations predicted that 99.5% of our patients receiving doubled doses of lopinavir/ritonavir achieve morning trough concentrations of lopinavir > 1 mg l(-1) during rifampicin co-administration, and 95% of those weighing less than 50 kg achieve this target already with 600/150 mg doses of lopinavir/ritonavir.

CONCLUSIONS

The model describes the drug-drug interactions between lopinavir, ritonavir and rifampicin in adults. The higher trough concentrations observed in the morning were explained by both higher bioavailability with the evening meal and lower clearance overnight.

[New strategies in the optimisation of lopinavir/ritonavir doses in human immunodeficiency virus-infected patients]

Lopinavir/ritonavir (LPV/r) has demonstrated virological and immunological efficacy in the combined antiretroviral treatment (cART), in both naïve and experienced patients. Furthermore, LPV/r showed a high barrier to the development of resistance. Although generally well tolerated, adverse gastrointestinal side effects and metabolic disorders are frequent. The different tools used to optimise the cART with this drug combination in the daily clinical practice, emphasising the therapeutic drug monitoring (TDM) of LPV/r and the genetic analysis of the main enzymes responsible for the metabolism and transport, are reviewed. The relationship between phenotype and genotype, established through TDM, could be useful for the physician to improve the clinical management of the HIV infection, due to the possibility of individualising the dose with this drug. Monotherapy is also reviewed as a new strategy used in the simplification of the treatment with this drug, which could increase safety and reduce costs.

Population pharmacokinetics of lopinavir/ritonavir (Kaletra) in HIV-infected patients

BACKGROUND

A relationship between plasma concentrations and viral suppression in patients receiving lopinavir (LPV)/ritonavir (RTV) has been observed. Therefore, it is important to increase our knowledge about factors that determine interpatient variability in LPV pharmacokinetics (PK).

METHODS

The study, designed to develop and validate population PK models for LPV and RTV, involved 263 ambulatory patients treated with 400/100 mg of LPV/RTV twice daily. A database of 1110 concentrations of LPV and RTV (647 from a single time-point and 463 from 73 full PK profiles) was available. Concentrations were determined at steady state using high-performance liquid chromatography with ultraviolet detection. PK analysis was performed with NONMEM software. Age, gender, height, total body weight, body mass index, RTV trough concentration (RTC), hepatitis C virus coinfection, total bilirubin, hospital of origin, formulation and concomitant administration of efavirenz (EFV), saquinavir (SQV), atazanavir (ATV), and tenofovir were analyzed as possible covariates influencing LPV/RTV kinetic behavior.

RESULTS

Population models were developed with 954 drug plasma concentrations from 201 patients, and the validation was conducted in the remaining 62 patients (156 concentrations). A 1-compartment model with first-order absorption (including lag-time) and elimination best described the PK. Proportional error models for interindividual and residual variability were used. The final models for the drugs oral clearance (CL/F) were as follows: CL/F(LPV)(L/h)=0.216·BMI·0.81(RTC)·1.25(EFV)·0.84(ATV); CL/F(RTV)(L/h) = 8.00·1.34(SQV)·1.77(EFV)·1.35(ATV). The predictive performance of the final population PK models was tested using standardized mean prediction errors, showing values of 0.03 ± 0.74 and 0.05 ± 0.91 for LPV and RTV, and normalized prediction distribution error, confirming the suitability of both models.

CONCLUSIONS

These validated models could be implemented in clinical PK software and applied to dose individualization using a Bayesian approach for both drugs.

Population pharmacokinetics of intravenously and orally administered docetaxel with or without co-administration of ritonavir in patients with advanced cancer

AIM

Docetaxel has a low oral bioavailability due to affinity for P-glycoprotein and cytochrome P450 (CYP) 3A4 enzymes. Inhibition of the CYP3A4 enzymes by ritonavir resulted in increased oral bioavailability. The aim of this study was to develop a population pharmacokinetic (PK) model and to evaluate and quantify the influence of ritonavir on the PK of docetaxel.

METHODS

Data from two clinical trials were included in the data analysis, in which docetaxel (75 mg m(-2) or 100 mg) had been administered intravenously or orally (10 mg or 100 mg) with or without co-administration of oral ritonavir (100 mg). Population modelling was performed using non-linear mixed effects modelling. A three-compartment model was used to describe the i.v. data. PK data after oral administration, with or without co-administration of ritonavir, were incorporated into the model.

RESULTS

Gut bioavailability of docetaxel increased approximately two-fold from 19 to 39% (CV 13%) with ritonavir co-administration. The hepatic extraction ratio and the elimination rate of docetaxel were best described by estimating the intrinsic clearance. Ritonavir was found to inhibit in a concentration dependent manner the intrinsic clearance of docetaxel, which was described by an inhibition constant of 0.028 microg ml(-1) (CV 36%). A maximum inhibition of docetaxel clearance of more then 90% was reached.

CONCLUSIONS

A PK model describing both the PK of orally and intravenously administered docetaxel in combination with ritonavir, was successfully developed. Co-administration of ritonavir lead to increased oral absorption and reduced elimination rate of docetaxel.

Intracellular and plasma steady-state pharmacokinetics of raltegravir, darunavir, etravirine and ritonavir in heavily pre-treated HIV-infected patients

AIM

To study the steady-state plasma and intracellular pharmacokinetics of raltegravir, etravirine, darunavir and ritonavir in heavily pre-treated patients.

METHODS

Patients on a salvage regimen containing raltegravir, etravirine, darunavir and ritonavir were eligible for inclusion. During a 12 h dosing interval plasma and peripheral blood mononuclear cells were collected. Drug concentrations were measured using a validated LC-MS/MS assay and pharmacokinetic analysis was performed using non-linear mixed effect modelling.

RESULTS

Irregular absorption was observed with raltegravir and darunavir, which may be caused by enterohepatic cycling. Relative bioavailability of ritonavir was low, when compared with other ritonavir regimens. Raltegravir plasma pharmacokinetics showed wide interpatient variability, while intracellular raltegravir concentrations could not be detected (<0.001 mg l(-1) in cell lysate). The intracellular to plasma ratios for etravirine, darunavir and ritonavir were 12.9, 1.32 and 7.72, respectively, and the relative standard error of these estimates were 16.3%, 12.3% and 13.0%.

CONCLUSIONS

The observed distinct intracellular accumulation indicated that these drugs have different affinity for the cellular compartment. The relatively high intracellular accumulation of etravirine may explain its efficacy and its previously described absence of PK-PD relationships in the therapeutic concentration range, when compared with other non-nucleoside reverse transcriptase inhibitors. Lastly, the intracellular concentrations of ritonavir seem sufficient for inhibition of viral replication in the cellular compartment in PI-naive patients, but not in patients with HIV harbouring PI resistance.

Population pharmacokinetics of lopinavir in combination with rifampicin-based antitubercular treatment in HIV-infected South African children

PURPOSE

The population pharmacokinetics (PK) of lopinavir in tuberculosis (TB)/human immunodeficiency virus (HIV) co-infected South African children taking super-boosted lopinavir (lopinavir/ritonavir ratio 1:1) as part of antiretroviral treatment in the presence of rifampicin were compared with the population PK of lopinavir in HIV-infected South African children taking standard doses of lopinavir/ritonavir (ratio 4:1).

METHODS

Lopinavir concentrations were measured in 15 TB/HIV-co-infected paediatric patients who were sampled during and after rifampicin-based TB treatment and in 15 HIV-infected children without TB. During TB therapy, the dose of ritonavir was increased to lopinavir/ritonavir 1:1 in order to compensate for the induction of rifampicin. The children received median (interquartile range=IQR) doses of lopinavir 292 mg/m(2) (274, 309) and ritonavir 301 mg/m(2) (286, 309) twice daily. After TB treatment completion the children received standard doses of lopinavir/ritonavir 4:1 (median [IQR] lopinavir dose 289 mg/m(2) [286, 303] twice daily) as did those without TB (median [IQR] lopinavir dose 265 mg/m(2) [249, 289] twice daily).

RESULTS

Lopinavir oral clearance (CL/F) was about 30% lower in children without TB than in co-infected children treated with super-boosted lopinavir. However, the predicted lopinavir C(min) was above the recommended minimum therapeutic concentration during TB/HIV co-treatment in the 15 children. Lopinavir CL/F increased linearly during the dosing interval.

CONCLUSIONS

Increasing the ritonavir dose to achieve a lopinavir/ritonavir ratio of 1:1 when given in combination with rifampicin-based TB treatment did not completely compensate for the enhancement of lopinavir CL/F caused by rifampicin. The time-dependent lopinavir CL/F might be due to a time-dependent recovery from ritonavir inhibition of lopinavir metabolism during the dosing interval.

Age-related changes in plasma concentrations of the HIV protease inhibitor lopinavir

The advent of highly active antiretroviral therapy in the treatment of HIV disease has substantially extended the lifespan of individuals infected with HIV resulting in a growing population of older HIV-infected individuals. The efficacy and safety of antiretroviral agents in the population are important concerns. There have been relatively few studies assessing antiretroviral pharmacokinetics in older patients. Thirty-seven subjects aged 18-30 years and 40 subjects aged 45-79 years, naive to antiretroviral therapy, received lopinavir/ritonavir (400/100) bid, emtricitibine 200 mg qd, and stavudine 40 mg bid. Trough lopinavir concentrations were available for 44 subjects, collected at 24, 36, and 96 weeks. At week 24, older age was associated with higher lopinavir trough concentrations, and a trend was observed toward older age being associated with higher lopinavir trough concentrations when all time points were evaluated. In the young cohort, among subjects with two or more measurements, there was a trend toward increasing intrasubject trough lopinavir concentrations over time. Using a nonlinear, mixed-effects population pharmacokinetic model, age was negatively associated with lopinavir clearance after adjusting for adherence. Adherence was assessed by patient self-reports; older patients missed fewer doses than younger patients (p = 0.02). No difference in grade 3-4 toxicities was observed between the two age group. Older patients have higher trough lopinavir concentrations and likely decreased lopinavir clearance. Age-related changes in the pharmacokinetics of antiretroviral drugs may be of increasing importance as the HIV-infected population ages and as older individuals comprise an increasing proportion of new diagnoses.

Pharmacokinetics and pharmacodynamics of GS-9350: a novel pharmacokinetic enhancer without anti-HIV activity

GS-9350 is a new chemical entity under development as a potent, mechanism-based inhibitor of human cytochrome P450 3A (CYP3A) isoforms. Its intended use is to increase the systemic exposure of coadministered agents that are metabolized by CYP3A enzymes. Unlike ritonavir, which is in current clinical use for this purpose, GS-9350 is devoid of anti-HIV activity. The pharmacokinetics of GS-9350 and its efficacy in increasing systemic exposure of the probe CYP3A substrate midazolam were examined in a study involving single- and multiple-dose escalations of GS-9350 from 50 to 400 mg. Single-dose escalation from 50 to 400 mg resulted in a 164-fold increase in GS-9350 exposure, whereas multiple-dose escalation in the dosage range of 50-300 mg resulted in a 47-fold increase in exposure. GS-9350 potently inhibited midazolam apparent clearance (95% reduction), similar in effect to ritonavir 100 mg. GS-9350 was generally well tolerated at all doses, and there was no evidence of dose-limiting toxicity. Establishing proof-of-concept, GS-9350 is currently under phase II development as a potential alternative to ritonavir for use with antiretroviral agents (including the HIV integrase inhibitor elvitegravir) that are often prescribed along with a "booster" drug.

Influence of pharmacogenetics on indinavir disposition and short-term response in HIV patients initiating HAART

AIMS

To assess the relationship between genetic polymorphisms and indinavir pharmacokinetic variability and to study the link between concentrations and short-term response or metabolic safety.

METHODS

Forty protease inhibitor-naive patients initiating highly active antiretroviral therapy (HAART) including indinavir/ritonavir and enrolled in the COPHAR 2-ANRS 111 trial were studied. At week 2, four blood samples were taken before and up to 6 h following drug intake. A population pharmacokinetic analysis was performed using the stochastic approximation expectation maximization (SAEM) algorithm implemented in MONOLIX software. The area under the concentration-time curve (AUC) and maximum (C(max)) and trough concentrations (C(trough)) of indinavir were derived from the population model and tested for their correlation with short-term viral response and safety measurements, while for ritonavir, these same three parameters were tested for their correlation with short-term biochemical safety

RESULTS

A one-compartment model with first-order absorption and elimination best described both indinavir and ritonavir concentrations. For indinavir, the estimated clearance and volume of distribution were 22.2 L/h and 97.3 L, respectively. The eight patients with the *1B/*1B genotype for the CYP3A4 gene showed a 70% decrease in absorption compared to those with the *1A/*1B or *1A/*1A genotypes (0.5 vs. 2.1, P = 0.04, likelihood ratio test by permutation). The indinavir AUC and C(trough) were positively correlated with the decrease in human immunodeficiency virus RNA between week 0 and week 2 (r = 0.4, P = 0.03 and r = -0.4, P = 0.03, respectively). Patients with the *1B/*1B genotype also had a significantly lower indinavir C(max) (median 3.6, range 2.1-5.2 ng/mL) than those with the *1A/*1B or *1A/*1A genotypes (median 4.4, range 2.2-8.3 ng/mL) (P = 0.04) and a lower increase in triglycerides during the first 4 weeks of treatment (median 0.1, range -0.7 to 1.4 vs. median 0.6, range -0.5 to 1.7 mmol/L, respectively; P = 0.02). For ritonavir, the estimated clearance and volume of distribution were 8.3 L/h and 60.7 L, respectively, and concentrations were not found to be correlated to biochemical safety. Indinavir and ritonavir absorption rate constants were found to be correlated, as well as their apparent volumes of distribution and clearances, indicating correlated bioavailability of the two drugs.

CONCLUSION

The CYP3A4*1B polymorphism was found to influence the pharmacokinetics of indinavir and, to some extent, the biochemical safety of indinavir.

Simultaneous population pharmacokinetic model for lopinavir and ritonavir in HIV-infected adults

BACKGROUND

Lopinavir is a protease inhibitor indicated for the treatment of HIV infection. It is coformulated with low doses of ritonavir in order to enhance its pharmacokinetic profile. After oral administration, plasma concentrations of lopinavir can vary widely between different HIV-infected patients.

OBJECTIVE

To develop and validate a population pharmacokinetic model for lopinavir and ritonavir administered simultaneously in a population of HIV-infected adults. The model sought was to incorporate patient characteristics influencing variability in the drug concentration and the interaction between the two compounds.

METHODS

HIV-infected adults on stable therapy with oral lopinavir/ritonavir in routine clinical practice for at least 4 weeks were included. A concentration-time profile was obtained for each patient, and blood samples were collected immediately before and 1, 2, 4, 6, 8, 10 and 12 hours after a morning lopinavir/ritonavir dose. Lopinavir and ritonavir concentrations in plasma were determined by high-performance liquid chromatography. First, a population pharmacokinetic model was developed for lopinavir and for ritonavir separately. The pharmacokinetic parameters, interindividual variability and residual error were estimated, and the influence of different patient characteristics on the pharmacokinetics of lopinavir and ritonavir was explored. Then, a simultaneous model estimating the pharmacokinetics of both drugs together and incorporating the influence of ritonavir exposure on oral clearance (CL/F) of lopinavir was developed. Population analysis was performed using nonlinear mixed-effects modelling (NONMEM version V software). The bias and precision of the final model were assessed through Monte Carlo simulations and data-splitting techniques.

RESULTS

A total of 53 and 25 Caucasian patients were included in two datasets for model building and model validation, respectively. Lopinavir and ritonavir pharmacokinetics were described by one-compartment models with first-order absorption and elimination. The presence of advanced liver fibrosis decreased CL/F of ritonavir by nearly half. The volume of distribution after oral administration (Vd/F) and CL/F of lopinavir were reduced as alpha1-acid glycoprotein (AAG) concentrations increased. CL/F of lopinavir was inhibited by ritonavir concentrations following a maximum-effect model (maximum inhibition [Imax] = 1, concentration producing 50% of the I(max) [IC50] = 0.36 mg/L). The final model appropriately predicted plasma concentrations in the model-validation dataset with no systematic bias and adequate precision.

CONCLUSION

A population model to simultaneously describe the pharmacokinetics of lopinavir and ritonavir was developed and validated in HIV-infected patients. Bayesian estimates of the individual parameters of ritonavir and lopinavir could be useful to predict lopinavir exposure based on the presence of advanced liver fibrosis and the AAG concentration in an individual manner, with the aim of maximizing the chances of treatment success.

Mechanism-based inhibition of cytochrome P450 enzymes: an evaluation of early decision making in vitro approaches and drug-drug interaction prediction methods

The ability to use in vitro human cytochrome P450 (CYP) time-dependent inhibition (TDI) data for in vivo drug-drug interaction (DDI) predictions should be viewed as a prerequisite to generating the data. Important terms in making such predictions are k(inact) and K(I) but first-line screening assays typically involve characterisation of an IC(50) value or a time dependent shift in IC(50). In the work presented here, two key screening methods from the scientific literature were appraised both in terms of practicality and quality of k(inact)/K(I) estimation. The utility of TDI screening data in DDI predictions was investigated and particular reference given to a simple DDI simulation model based on a spreadsheet that calculates the systemic exposure of unbound inhibitor drug following the input of human pharmacokinetic parameters. Using several clinical mechanism-based CYP DDI examples, the effectiveness of the approach was assessed and compared to other widely available approaches (a simple algorithm that employs a single in vivo unbound inhibitor concentration, a seven-compartment physiologically based pharmacokinetic (PBPK) model that defines the extent of interaction as a result of hepatic inhibitor concentrations and the commercially available software SimCYP). All the methods gave predictions that compared favourably with the observed DDIs, but various advantages and disadvantages of each were also given full consideration. The new model facilitates rapid sensitivity analysis (parameters can be easily input and altered to give a visual representation of the impact on the active enzyme concentration) and it was therefore used to derive "rules of thumb" demonstrating the relationship between extent of DDI, time-dependent IC(50) and dose for typical acidic and basic drugs. Additionally, a TDI decision tree linking into reactive metabolite investigations is proposed for use in a Drug Discovery setting.

Importance of characterizing determinants of variability in exposure: application to dasatinib in subjects with chronic myeloid leukemia

Characterizing the key determinants of variability in the exposure of orally administered drugs may be important in understanding the implications of exposure variability on clinical responses. In particular, partitioning overall variability into interoccasion variability (IOV) and interindividual variability (IIV) allows a better assessment of the clinical importance of exposure variability. The IOV characterizes the dose-to-dose variability in exposure within a subject and is likely to be less clinically relevant than IIV for chronically administered drugs as the effect of IOV averages out over repeated dosing. The main aims of this model-based analysis were (1) to characterize the IOV and IIV of dasatinib, a novel, orally administered, multitargeted kinase inhibitor of BCR-ABL and SRC family kinases that is indicated for the treatment of chronic myeloid leukemia and Philadelphia-positive acute lymphoblastic leukemia and (2) to demonstrate using simulated data that it is possible to estimate IIV and IOV in relative bioavailability (F(R)) of an orally administered drug, given an adequate sampling scheme. Variability in dasatinib exposure was estimated to be mainly due to IOV in F(R) (44% coefficient of variation [CV]) and, to a lesser extent, due to IIV in F(R) and IIV in clearance (32% and 25% CV, respectively). The IIV is expected to be more clinically relevant than IOV for chronically administered oral drugs such as dasatinib, as the overall variability in cumulative exposure will be mainly due to IIV. The analysis of simulated data demonstrated that models ignoring either IIV or IOV in F(R) resulted in upwardly biased estimates of interindividual or residual variability. Thus, it may be important to account for both IIV and IOV in F(R), particularly for orally administered agents that exhibit absorption-related variability in exposure.

Pharmacokinetic interaction between rifampicin and ritonavir-boosted atazanavir in HIV-infected patients

BACKGROUND

Tuberculosis (TB) is a common opportunistic infection among HIV-infected people, and rifampicin is an important drug for the treatment of TB. However, administration of rifampicin in combination with antiretroviral therapy, particularly protease inhibitors, is difficult because of drug-drug interactions.

METHODS

We have performed a prospective study in three HIV-infected patients with TB treated with a rifampicin-containing regimen (rifampicin 600 mg per day) and antiretroviral therapy including only nucleoside reverse transcriptase inhibitors (NRTIs) plus atazanavir 300 mg once a day (qd) and ritonavir 100 mg qd, to evaluate whether the inducing effect of rifampicin on the drug-metabolizing enzyme cytochrome P450 (CYP) 3A4 could be overcome by the inhibitory effect of ritonavir. A complete pharmacokinetic evaluation of the steady-state concentrations of atazanavir and ritonavir was performed.

RESULTS

In all three cases, more than 50% of the time the atazanavir level was below the minimum recommended trough plasma level (150 ng/mL according to current pharmacokinetic guidelines) to inhibit HIV wild-type replication.

CONCLUSION

These results strongly indicate that the administration of rifampicin with a combination of atazanavir 300 mg qd plus ritonavir 100 mg qd must be avoided because subtherapeutic concentrations of atazanavir are produced.

Population pharmacokinetics of valproate in Chinese children with epilepsy

AIM

The aim of the present study is to establish a population pharmacokinetic (PPK) model of valproate (VPA) in Chinese epileptic children to promote the reasonable use of anti-epileptic drugs.

METHODS

Sparse data of VPA serum concentrations from 417 epileptic children were collected. These patients were divided into 2 groups: the PPK model group (n=317) and the PPK valid group (n=100). The PPK parameter values of VPA were calculated by NONMEM software using the data of the PPK model group. A basic model and a final model were set up. To validate the 2 models, the concentrations of PPK valid group were predicted by each model, respectively. The mean prediction error (MPE), mean squared prediction error (MSPE), root mean squared prediction error (RMSPE), weight residues (WRES), and the 95% confidence intervals (95% CI) were also calculated. Then, the values between the 2 models were compared.

RESULTS

The PPK of VPA was determined by a 1-compartment model with a first-order absorption process. The basic model was: Ka=3.09 (h(-1)), V/F=20.4 (L), CL/F=0.296 (L/h). The final model was: Ka=0.251+2.24 x (1-HS) (h(-1)), V/F=2.88+0.157 x WT (L), CL/F=0.106(0.98 x CO)+ 0.0157 x AGE (L/h). For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -23.53 (-30.36, -16.70), 3728.96 (2872.72, 4585.20), 39.62 (34.34, 44.90), and -0.06 (-0.14, 0.02), respectively. For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -1.16 (-4.85, 2.53), 1002.83 (1050.64, 1143.61), 23.04 (21.12, 24.96), and 0.08 (-0.04, 0.20), respectively. The final model was more optimal than the basic model.

CONCLUSION

The PPK model of VPA in Chinese epileptic children was successfully established. It will be valuable to facilitate individualized dosage regimens.

ADME pathway approach for pharmacogenetic studies of anti-HIV therapy

Pharmacogenetics holds promise in HIV treatment because of the complexity and potential toxicity of multidrug therapies that are prescribed for long periods. However, there has been limited success with the current approach where one or few candidate genes are examined for a limited number of allelic variants. A change in paradigm emerges from the availability of the HapMap, the wealth of data on less common genetic polymorphisms, and new genotyping technology. We present a comprehensive review of functional and putative functional variants in genes encoding absorption, distribution, metabolism and excretion (ADME) proteins relevant to HIV therapy. We propose an analytical array based on our review of the literature, web resources and use of bioinformatic analysis. We identified 126 genes with proven or potential role in HIV therapy. Variation in these genes can be characterized by 2428 SNPs (in Caucasians). On average, a gene is covered by 20 SNPs. This review compiles information for future analysis of the role of specific genes/variants in the exposure and response to antiretroviral therapy to generate a ranked list of new genetic variants for future studies.

Gender-specific effects of HIV protease inhibitors on body mass in mice

Protease inhibitors, as part of highly active anti-retroviral therapy (HAART), have significantly increased the lifespan of human immunodeficiency virus (HIV) infected patients. Several deleterious side effects including dyslipidemia and lipodystrophy, however, have been observed with HAART. Women are at a higher risk of developing adipose tissue alterations and these alterations have different characteristics as compared to men. We have previously demonstrated that in mice the HIV protease inhibitor, ritonavir, caused a reduction in weight gain in females, but had no effect on male mice. In the present study, we examined the potential causes of this difference in weight gain. Low-density lipoprotein receptor (LDL-R) null mice or wild-type C57BL/6 mice, were administered 15 mug/ml ritonavir or vehicle (0.01% ethanol) in the drinking water for 6 weeks. The percent of total body weight gained during the treatment period was measured and confirmed that female LDL-R gained significantly less weight with ritonavir treatment than males. In wild type mice, however, there was no effect of ritonavir treatment in either sex. Despite the weight loss in LDL-R null mice, ritonavir increased food intake, but no difference was observed in gonadal fat weight. Serum leptin levels were significantly lower in females. Ritonavir further suppressed leptin levels in (p < 0.05). Ritonavir did not alter serum adiponectin levels in either gender. To determine the source of these differences, female mice were ovariectomized remove the gonadal sex hormones. Ovariectomy prevented the weight loss induced by ritonavir (p < 0.05). Furthermore, leptin levels were no longer suppressed by ritonavir (p < 0.05). This study demonstrates that gonadal factors in females influence the hormonal control of weight gain changes induced by HIV protease inhibitors in an environment of elevated cholesterol.

Population pharmacokinetics of lopinavir in combination with ritonavir in HIV-1-infected patients

AIMS

To develop a population pharmacokinetic model for lopinavir in combination with ritonavir, in which the interaction between both drugs was characterized, and in which relationships between patient characteristics and pharmacokinetics were identified.

METHODS

The pharmacokinetics of lopinavir in combination with ritonavir were described using NONMEM (version V, level 1.1). First, ritonavir data were fitted to a previously developed model to obtain individual Bayesian estimates of pharmacokinetic parameters. Hereafter, an integrated model for the description of the pharmacokinetics of lopinavir with ritonavir was designed.

RESULTS

From 122 outpatients 748 lopinavir and 748 ritonavir plasma concentrations were available for analysis. The interaction between the drugs was described by a time-independent inverse relationship between the exposure to ritonavir over a dosing-interval and the apparent clearance (CL/F) of lopinavir. The model parameters volume of distribution and absorption rate constant were 61.6 l (95% prediction interval (PI) 22.4, 83.7) and 0.564 h(-1) (95% PI 0.208, 0.947), respectively. The model yielded a theoretical value for the CL/F of lopinavir without ritonavir of 14.8 l h(-1) (95%PI 12.1, 20.1), which translates to a value of 5.73 l h(-1) in the presence of ritonavir. The only factor with significant effect on the pharmacokinetics was concurrent use of non-nucleoside reverse transcriptase inhibitors (NNRTI), which increased the CL/F of lopinavir by 39% (P < 0.001).

CONCLUSIONS

We have developed a model that has defined a time-independent inverse relationship between the exposure to ritonavir and the CL/F of lopinavir, and provided an adequate description of the pharmacokinetic parameters for the latter. Concomitant use of the NNRTIs efavirenz and nevirapine increased the CL/F of lopinavir.

Population pharmacokinetics of indinavir alone and in combination with ritonavir in HIV-1-infected patients

AIMS

The aim of the study was to characterize the population pharmacokinetics of indinavir, define the relationship between the pharmacokinetics of indinavir and ritonavir, and to identify the factors influencing the pharmacokinetics of indinavir alone or when given with ritonavir.

METHODS

HIV-1-infected patients being treated with an indinavir-containing regimen were included. During regular visits, 102 blood samples were collected for the determination of plasma indinavir and ritonavir concentrations. Full pharmacokinetic curves were available from 45 patients. Concentrations of indinavir and ritonavir were determined by liquid chromatography coupled with electrospray tandem mass spectrometry. Pharmacokinetic analysis was performed using nonlinear mixed effect modelling (NONMEM).

RESULTS

The disposition of indinavir was best described by a single compartment model with first order absorption and elimination. Values for the clearance, volume of distribution and the absorption rate constant were 46.8 l h(-1) (24.2% IIV), 82.3 l (24.6% IIV) and 02.62 h(-1), respectively. An absorption lag-time of 0.485 h was detected in patients also taking ritonavir. Furthermore this drug, independent of dose (100-400 mg) or plasma concentration, decreased the clearance of indinavir by 64.6%. In contrast, co-administration of efavirenz or nevirapine increased the clearance of indinavir by 41%, irrespective of the presence or absence of ritonavir. Female patients had a 48% higher apparent bioavailability of indinavir than males.

CONCLUSIONS

The pharmacokinetic parameters of indinavir were adequately described by our population model. Female gender and concomitant use of ritonavir and non-nucleoside reverse transcriptase inhibitors strongly influenced the pharmacokinetics of this drug. The results support the concept of ritonavir boosting, maximum inhibition of indinavir metabolized being observed at 100 mg.