Application and impact of population pharmacokinetics in the assessment of antiretroviral pharmacotherapy

Real-Life Therapeutic Concentration Monitoring of Long-Acting Cabotegravir and Rilpivirine: Preliminary Results of an Ongoing Prospective Observational Study in Switzerland

SHCS#879 is an ongoing Switzerland-wide multicenter observational study conducted within the Swiss HIV Cohort Study (SHCS) for the prospective follow-up of people living with HIV (PLWH) receiving long-acting injectable cabotegravir-rilpivirine (LAI-CAB/RPV). All adults under LAI-CAB/RPV and part of SHCS are enrolled in the project. The study addresses an integrated strategy of treatment monitoring outside the stringent frame of controlled clinical trials, based on relevant patient characteristics, clinical factors, potential drug-drug interactions, and measurement of circulating blood concentrations. So far, 91 blood samples from 46 PLWH have been collected. Most individuals are less than 50 years old, with relatively few comorbidities and comedications. The observed concentrations are globally in accordance with the available values reported in the randomized clinical trials. Yet, low RPV concentrations not exceeding twice the reported protein-adjusted 90% inhibitory concentration have been observed. Data available at present confirm a considerable between-patient variability overall. Based on the growing amount of PK data accumulated during this ongoing study, population pharmacokinetic analysis will characterize individual concentration-time profiles of LAI-CAB/RPV along with their variability in a real-life setting and their association with treatment response and tolerability, thus bringing key data for therapeutic monitoring and precision dosage adjustment of this novel long-acting therapy.

Drug Exposure to Establish Pharmacokinetic-Response Relationships in Oncology

In the oncology field, understanding the relationship between the dose administered and the exerted effect is particularly important because of the narrow therapeutic index associated with anti-cancer drugs and the high interpatient variability. Therefore, in this review, we provide a critical perspective of the different methods of characterising treatment exposure in the oncology setting. The increasing number of modelling applications in oncology reflects the applicability and the impact of pharmacometrics on all phases of the drug development process and patient management as well. Pharmacometric modelling is a worthy component within the current paradigm of model-based drug development, but pharmacometric modelling techniques are also accessible for the clinician in the optimisation of current oncology therapies. Consequently, the application of population models in a hospital setting by generating close collaborations between physicians and pharmacometricians is highly recommended, providing a systematic means of developing and assessing model-based metrics as 'drivers' for various responses to treatments, which can then be evaluated as predictors for treatment success. Characterising the key determinants of variability in exposure is of particular importance for anticancer agents, as efficacy and toxicity are associated with exposure. We present the different strategies to describe and predict drug exposure that can be applied depending on the data available, with the objective of obtaining the most useful information in the patients' favour throughout the full drug cycle. Therefore, the objective of the present article is to review the different approaches used to characterise a patient's exposure to oncology drugs, which will result in a better understanding of the time course of the response and the magnitude of interpatient variability.

Population pharmacokinetics of Rilpivirine in HIV-1-infected patients treated with the single-tablet regimen rilpivirine/tenofovir/emtricitabine

PURPOSE

Rilpivirine, prescribed for the treatment of HIV infection, presents an important inter-individual pharmacokinetic variability. We aimed to determine population pharmacokinetic parameters of rilpivirine in adult HIV-infected patients and quantify their inter-individual variability.

METHODS

We conducted a multicenter, retrospective, and observational study in patients treated with the once-daily rilpivirine/tenofovir disoproxil fumarate/emtricitabine regimen. As part of routine therapeutic drug monitoring, rilpivirine concentrations were measured by UPLC-MS/MS. Population pharmacokinetic analysis was performed using NONMEM software. Once the compartmental and random effects models were selected, covariates were tested to explain the inter-individual variability in pharmacokinetic parameters. The final model qualification was performed by both statistical and graphical methods.

RESULTS

We included 379 patients, resulting in the analysis of 779 rilpivirine plasma concentrations. Of the observed trough individual plasma concentrations, 24.4% were below the 50 ng/ml minimal effective concentration. A one-compartment model with first-order absorption best described the data. The estimated fixed effect for plasma apparent clearance and distribution volume were 9 L/h and 321 L, respectively, resulting in a half-life of 25.2 h. The common inter-individual variability for both parameters was 34.1% at both the first and the second occasions. The inter-individual variability of clearance was 30.3%.

CONCLUSIONS

Our results showed a terminal half-life lower than reported and a high proportion of patients with suboptimal rilpivirine concentrations, which highlights the interest of using therapeutic drug monitoring in clinical practice. The population analysis performed with data from "real-life" conditions resulted in reliable post hoc estimates of pharmacokinetic parameters, suitable for individualization of dosing regimen.

Comparison of Population Pharmacokinetics Based on Steady-State Assumption Versus Electronically Monitored Adherence to Lopinavir, Atazanavir, Efavirenz, and Etravirine: A Retrospective Study

BACKGROUND

Population pharmacokinetic (PopPK) analyses often rely on steady state and full adherence to prescribed dosage regimen assumptions from data gathered during therapeutic drug monitoring (TDM). Nonadherence is common in chronic diseases such as HIV. This study evaluates the impact of adherence measurement by electronic monitoring on PopPK parameter estimation and individual concentration profile predictions, and also the influence of adherence issues on the clinical interpretation of a concentration measurement.

METHODS

Published PopPK models for lopinavir, atazanavir, efavirenz, and etravirine were applied to estimate PK parameters and individual concentrations in 140 HIV patients taking part in a medication adherence program using 2 dosing data sets. The first set included the last dose reported by the patient with steady-state and full adherence assumptions; the second set used detailed electronic dosing history. PopPK parameter estimates and individual predictions were compared between the 2 dosing entries.

RESULTS

Clearance estimates and likewise predicted concentrations did not markedly differ between the 2 dosing histories. However, certain patterns of nonadherence such as sparse missed doses or consecutive missed doses lead to suboptimal drug exposure. The interpretation based on self-reported information would have concluded on a wrongly appropriate individual exposure.

CONCLUSIONS

PopPK analysis assuming steady state with full adherence produced similar results to those based on detailed electronic dosing history reconciled with patients' allegations. Self-reported last dose intake appeared reliable for concentration predictions and therapeutic drug monitoring interpretation for most patients followed at the medication adherence program. Yet, clinicians should be aware that concentration predictions based on self-reported last dose intake might be overestimated in case of undetected patterns of nonadherence, increasing the risk of forthcoming therapeutic failure.

Antiretroviral pharmacology in mucosal tissues

Strategies to prevent HIV infection using preexposure prophylaxis are required to curtail the HIV pandemic. The mucosal tissues of the genital and rectal tracts play a critical role in HIV acquisition, but antiretroviral (ARV) disposition and correlates of efficacy within these tissues are not well understood. Preclinical and clinical strategies to describe ARV pharmacokinetic-pharmacodynamic relationships within mucosal tissues are currently being investigated. In this review, we summarize the physicochemical and biologic factors influencing ARV tissue exposure. Furthermore, we discuss the necessary steps to generate relevant pharmacokinetic-pharmacodynamic data and the challenges associated with this process. Finally, we suggest how preclinical and clinical data might be practically translated into optimal preexposure prophylaxis dosing strategies for clinical trials testing using mathematical modeling and simulation.

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.

In vivo-in vitro-in silico pharmacokinetic modelling in drug development: current status and future directions

Although clinical drug trials are indispensable in providing an appropriate background for dosage recommendations, they can provide mechanistic pharmacokinetic information only indirectly with the help of certain biomarkers for pathological, physiological and pharmacological determinants. Thus, to provide such mechanistic information of clinical value, various in vitro and in silico tests and approaches are increasingly employed in drug discovery and development. Integration of the results of these primarily preclinical studies has been made possible by various computational models, such as in vitro-in vivo extrapolation of hepatic clearance or physiologically based pharmacokinetic modelling. In this article, the current status of these modelling approaches is surveyed and some examples are given, highlighting advantages and disadvantages in applying them at various phases of drug development. A new paradigm of model-based drug development is briefly described, and the importance of the approach of integrating all of the information coming from different investigations at all levels--be it in vivo, in vitro or in silico--is emphasized.

Physiologically based modelling and prediction of drug interactions

A major challenge for drug development and environmental or occupational health is the prediction of pharmacokinetic and pharmacodynamic interactions between drugs, natural chemicals or environmental contaminants. This article reviews briefly past developments in the area of physiologically based pharmacokinetic (PBPK) modelling of interactions. It also demonstrates a systems biology approach to the question, and the capabilities of new software tools to facilitate that development. Individual Systems Biology Markup Language models of metabolic pathways can now be automatically merged and coupled to a template PBPK pharmacokinetic model, using for example the GNU MCSim software. The global model generated is very efficient and able to simulate the interactions between a theoretically unlimited number of substances. Development time and the number of model parameter increase only linearly with the number of substances considered, even though the number of possible interactions increases exponentially.

Cytochrome P450 3A inhibition by atazanavir and ritonavir, but not demography or drug formulation, influences saquinavir population pharmacokinetics in human immunodeficiency virus type 1-infected adults

Inadequate concentrations of the human immunodeficiency virus (HIV) protease inhibitor saquinavir jeopardize individual therapy success or produce side effects despite treatment according to the current guidelines. We performed a population pharmacokinetic analysis with NONMEM and determined that the steady-state pharmacokinetics of saquinavir in 136 HIV type 1-infected adults was modulated by a decrease in saquinavir CL following coadministration of the cytochrome P450 3A inhibitors ritonavir and atazanavir. In contrast, age, sex, weight, pregnancy, and the pharmaceutical formulation exerted only minor, nonsignificant effects.

Influence of the cytochrome P450 2B6 genotype on population pharmacokinetics of efavirenz in human immunodeficiency virus patients

A population pharmacokinetic model for efavirenz has been developed from therapeutic drug monitoring data in human immunodeficiency virus (HIV)-positive patients by using a nonlinear mixed-effect model. The efavirenz plasma concentrations (n = 375) of 131 patients were analyzed using high-performance liquid chromatography with UV detection. Pharmacokinetic parameters were estimated according to a one-compartment model. The effects of sex, age, total body weight, height, body mass index, and HIV treatment were analyzed. In a subgroup of 32 patients, genetic polymorphisms of the cytochrome P450 2B6 gene (CYP2B6), CYP3A4, and MDR1 were also investigated. Efavirenz oral clearance and the apparent volume of distribution were 9.50 liters/h and 311 liters, respectively. The model included only the effect of CYP2B6 polymorphisms on efavirenz clearance; this covariate reduced the intersubject variability of clearance by about 27%. Patients showing G/T and T/T CYP2B6 polymorphisms exhibited efavirenz clearances that were about 50% and 75% lower than those observed in the patients without these polymorphisms (G/G). Accordingly, to obtain EFV steady-state concentrations within the therapeutic range (1 to 4 mg/liter), it would be advisable to implement a gradual reduction in dose to 400 or 200 mg/day for patients that are intermediate or poor metabolizers, respectively. However, the remaining interindividual variability observed in the pharmacokinetic parameters of the model highlights the need for dose individualization to avoid inadequate exposure to efavirenz and suggests that these recommended doses be used with caution and confirmed by therapeutic drug monitoring and clinical efficacy. The population model can be implemented in pharmacokinetic clinical software for dosage optimization by using the Bayesian approach.

Nonnucleoside reverse transcriptase inhibitor pharmacokinetics in a large unselected cohort of HIV-infected women

BACKGROUND

Small intensive pharmacokinetic (PK) studies of medications in early-phase trials cannot identify the range of factors that influence drug exposure in heterogenous populations. We performed PK studies in large numbers of HIV-infected women on nonnucleoside reverse transcriptase inhibitors (NNRTIs) under conditions of actual use to assess patient characteristics that influence exposure and evaluated the relationship between exposure and response.

METHODS

Two hundred twenty-five women on NNRTI-based antiretroviral regimens from the Women's Interagency HIV Study were enrolled into 12-hour or 24-hour PK studies. Extensive demographic, laboratory, and medication covariate data were collected before and during the visit to be used in multivariate models. Total NNRTI drug exposure was estimated by area under the concentration-time curves.

RESULTS

Hepatic inflammation and renal insufficiency were independently associated with increased nevirapine exposure in multivariate analysis: crack cocaine, high fat diets, and amenorrhea were associated with decreased levels (n = 106). Higher efavirenz exposure was seen with increased transaminase, albumin levels, and orange juice consumption; tenofovir use, increased weight, being African American, and amenorrhea were associated with decreased exposure (n = 119). With every 10-fold increase in nevirapine or efavirenz exposure, participants were 3.3 and 3.6 times likely to exhibit virologic suppression, respectively. Patients with higher drug exposure were also more likely to report side effects on therapy.

CONCLUSIONS

Our study identifies and quantitates previously unrecognized factors modifying NNRTI exposure in the "real-world" setting. Comprehensive PK studies in representative populations are feasible and may ultimately lead to dose optimization strategies in patients at risk for failure or adverse events.

Model-based approach to characterize efavirenz autoinduction and concurrent enzyme induction with carbamazepine

Characterization of the time course and magnitude of enzyme induction due to multiple inducers is important for interpretation of clinical data from drug-drug interaction studies. A population interaction model was developed to quantify efavirenz autoinduction and further induction with concurrent carbamazepine coadministration. Efavirenz concentration data in the absence and presence of carbamazepine following single- and multiple-dose oral administrations in healthy subjects were used for model development. The proposed model was able to describe the time-dependent efavirenz autoinduction and the further induction with carbamazepine when the agents were combined. The estimated population averages of efavirenz oral clearance were 5.5, 9.4, 14.4, and 16.7 liters/h on days 1, 14, and 35 and at steady state for the interaction, respectively, for efavirenz monotherapy for 2 weeks followed by the coadministration of carbamazepine for 3 weeks. The estimated times to 50% of the steady state for efavirenz autoinduction and for the induction resulting from the concurrent administration of efavirenz and carbamazepine were similar (around 10 to 12 days). With this model-based analysis, efavirenz exposures can be projected prior to and at the steady state of induction, allowing a better understanding of the time course and magnitude of enzyme induction.

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.

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.

Lack of an effect of human immunodeficiency virus coinfection on the pharmacokinetics of entecavir in hepatitis B virus-infected patients

Entecavir is a guanosine nucleoside analogue approved for the treatment of chronic hepatitis B virus (HBV) infection. The impact of human immunodeficiency virus (HIV) coinfection on the pharmacokinetics (PK) of entecavir was examined by nonlinear mixed-effects modeling. Plasma concentration data from HIV- and HBV-coinfected patients were analyzed in conjunction with data from HBV-monoinfected patients, and HIV coinfection was tested as a covariate on oral clearance (CL/F). The estimated population averages of intercompartmental clearance and the volumes of distribution in the central and peripheral compartments obtained with a 1-mg dose were 34.2 liters/h (interindividual variability, 30.2%), 115 liters (interindividual variability, 39.2%), and 1,830 liters (interindividual variability, 74%), respectively. CL/F was found to be a function of creatinine clearance, but HIV confection did not show any effect on CL/F. The geometric mean (GM) of individual Bayesian estimates of the steady-state area under the concentration-time curve following 1-mg daily doses were 39.3 and 38.8 ng x h/ml in HIV- and HBV-coinfected and HBV-monoinfected patients, respectively. The adjusted GM ratio (1.01; 90% confidence interval, 0.91 to 1.12) was within the bioequivalence criteria boundary (0.80 to 1.25). In conclusion, the proposed model adequately described the entecavir PK in HBV- and HIV-coinfected patients and HBV-monoinfected patients, and the entecavir exposures were comparable in the two patient populations.

Facilitating compound progression of antiretroviral agents via modeling and simulation

Pharmacotherapy in human immunodeficiency virus (HIV)-infected patients and the development of safe and effective antiretroviral dosing regimens has been hindered by numerous issues, including the rapid development of viral resistance to drug therapy, the narrow therapeutic window of the drug compounds, and lack of fundamental knowledge concerning the sources of variation in exposure and response to antiretroviral agents. Sources of variation may include factors such as interpatient differences in genetic expression, immunological response, pathogenesis, epidemiologic and socioeconomic factors, and demographics. Modeling and simulation (M&S) techniques have become valuable tools to identify and quantify variability in exposure and response to antiretroviral agents throughout the drug development process. Before actual entry into human safety and pharmacokinetic (PK) trials, in vitro screening and in vivo pharmacology studies conducted to assess compound potency and compatibility with agents included in acceptable antiretroviral therapy (ART) regimens can be characterized via quantitative relationships. In addition, physiochemical data is initially used to screen drug candidates based on favorable PK and biopharmaceutic properties. Compound progression can likewise be supported with M&S exercises to ensure the traceability of key assumptions and decisions. The underlying techniques utilize nonlinear mixed effect modeling, Monte Carlo simulation, Neural networks, several regression-based approaches, and less computationally intensive techniques. The application of such an approach promises to be an essential component in the development of new agents to treat HIV-1 and is being implemented in the context of evaluating Nk1r antagonists as potential candidates to treat NeuroAIDS.

A comparison of the steady-state pharmacokinetics of nevirapine in men, nonpregnant women and women in late pregnancy

AIMS

To evaluate the pharmacokinetics of nevirapine and any possible influencing factors in pregnant women (n = 16), nonpregnant women (n = 13) and men (n = 14), who received nevirapine 200 mg twice daily together with nucleoside reverse transcriptase inhibitors.

METHODS

Blood samples were taken for 12 h at steady state. Nevirapine concentrations were measured by liquid chromatography-tandem mass spectrometry. The influence of gender, age, body weight and comedication on minimum and maximum concentrations (C(min), C(max)), area under the concentration-time curve (AUC), total clearance (CL(tot)), half-life (t(1/2)) and volume of distribution (V(d)) was analysed by multivariate techniques.

RESULTS

Mean [95% confidence interval (CI)]C(max), AUC(ss) and clearance were 5221 ng ml(-1) (4267, 6175), 50 789 ng (-1)h ml(-1) (43 453, 58 125) and 69.9 ml min(-1) for men, 5871 ng ml(-1) (4848, 6895), 57 045 ng h(-1) ml(-1) (45 997, 68 093) and 65.6 ml min(-1) for nonpregnant women and 4505 ng ml(-1) (3644, 5366), 44 579 ng h(-1) ml(-1) (36 564, 52 594) and 82.1 ml min(-1) for pregnant women. The differences between pregnant and nonpregnant women (% difference, 95% CI) in C(max) (-30.3; -28.5, -33.0), AUC(ss) (-28.0; - 25.8, - 29.5) and clearance (20.2; 26.6, 15.6) reached statistical significance (P = 0.010, P = 0.028 and P = 0.028, respectively). The multivariate analysis underscored the influence of bodyweight on the plasma exposure to nevirapine.

CONCLUSIONS

Pregnant women exhibited an increased nevirapine clearance and comparably low plasma concentrations, whereas women with a low bodyweight achieved high plasma nevirapine concentrations. The large variability in nevirapine concentrations in women may lead to loss of efficacy and viral resistance, or drug toxicity, and therefore these patients should be monitored frequently.